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changwookjun/nlp-paper

NLP Paper

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From the README

NLP Paper

natural language processing paper list

Contents

Bert Series
Transformer Series
Transfer Learning
Text Summarization
Sentiment Analysis
Question Answering
Machine Translation
Surver paper
Downstream task
- QA MC Dialogue
- Slot filling
- Analysis
- Word segmentation parsing NER
- Pronoun coreference resolution
- Word sense disambiguation
- Sentiment analysis
- Relation extraction
- Knowledge base
- Text classification
- WSC WNLI NLI
- Commonsense
- Extractive summarization
- IR
Generation
Quality evaluator
Modification (multi-task, masking strategy, etc.)
Probe
Multi-lingual
Other than English models
Domain specific
Multi-modal
Model compression
LLM
Reasoning and Chain of Thought
Alignment and RLHF
Retrieval Augmented Generation
LLM Agents and Tool Use
Long Context and Efficient Architectures
Efficient Training Inference and Serving
Pretraining Data Scaling Laws and Model Merging
Prompting and In Context Learning
Code LLM
Evaluation and Benchmark
Safety Hallucination and Interpretability
Misc

Bert Series

Transformer Series

Transfer Learning

Text Summarization

Sentiment Analysis

Question Answering

Machine Translation

The Evolved Transformer - David R. So(2019)

Surver paper

Evolution of transfer learning in natural language processing
Pre-trained Models for Natural Language Processing: A Survey
A Survey on Contextual Embeddings
A Survey of Large Language Models (FrontComputSci2026)
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond (arXiv 2023)
A Survey on Model Compression for Large Language Models (TACL)
Efficient Large Language Models: A Survey (arXiv 2023)
Large Language Models: A Survey (arXiv 2024)
A Survey on Post-training of Large Language Models (arXiv 2025)
The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook (arXiv 2026)
World Action Models: A Survey (arXiv 2026)

Downstream task

QA MC Dialogue

Slot filling

Analysis

Word segmentation parsing NER

Pronoun coreference resolution

Word sense disambiguation

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (EMNLP2019)
Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations (EMNLP2019)
Using BERT for Word Sense Disambiguation
Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation (ACL2019)
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings (KONVENS2019)

Sentiment analysis

Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence (NAACL2019)
BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis (NAACL2019)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis (EMNLP2019 WS)
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification
An Investigation of Transfer Learning-Based Sentiment Analysis in Japanese (ACL2019)
"Mask and Infill" : Applying Masked Language Model to Sentiment Transfer
Adversarial Training for Aspect-Based Sentiment Analysis with BERT
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language Inference
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language Inference

Relation extraction

Knowledge base

Text classification

WSC WNLI NLI

Commonsense

Extractive summarization

IR

Generation

Quality evaluator

Modification (multi-task, masking strategy, etc.)

Probe

Multi-lingual

Multilingual Constituency Parsing with Self-Attention and Pre-Training (ACL2019)
Language Model Pretraining (NeurIPS2019) [github]
75 Languages, 1 Model: Parsing Universal Dependencies Universally (EMNLP2019) [github]
Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations (EMNLP2019 WS)
Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT (EMNLP2019)
How multilingual is Multilingual BERT? (ACL2019)
How Language-Neutral is Multilingual BERT?
Is Multilingual BERT Fluent in Language Generation?
Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks (EMNLP2019)
BERT is Not an Interlingua and the Bias of Tokenization (EMNLP2019 WS)
Cross-Lingual Ability of Multilingual BERT: An Empirical Study (ICLR2020)
Multilingual Alignment of Contextual Word Representations (ICLR2020)
On the Cross-lingual Transferability of Monolingual Representations
Unsupervised Cross-lingual Representation Learning at Scale
Emerging Cross-lingual Structure in Pretrained Language Models
Can Monolingual Pretrained Models Help Cross-Lingual Classification?
Fully Unsupervised Crosslingual Semantic Textual Similarity Metric Based on BERT for Identifying Parallel Data (CoNLL2019)
What the [MASK]? Making Sense of Language-Specific BERT Models
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer (ACL2021) [github]
KLUE: Korean Language Understanding Evaluation (arXiv 2021)
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers (EMNLP2021)
Crosslingual Generalization through Multitask Finetuning (ACL2023)
MEGA: Multilingual Evaluation of Generative AI (EMNLP2023)
Language Model Tokenizers Introduce Unfairness Between Languages (NeurIPS2023)
A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean Language Models (arXiv 2023)
KoBBQ: Korean Bias Benchmark for Question Answering (TACL)
Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models (arXiv 2023)
HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models (LREC-COLING2024)
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models (ICLR2024)
AceGPT, Localizing Large Language Models in Arabic (NAACL2024)
Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model (arXiv 2023)
SeaLLMs -- Large Language Models for Southeast Asia (ACL2024)
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model (ACL2024)
KMMLU: Measuring Massive Multitask Language Understanding in Korean (NAACL2025)
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge (ACL2024 Findings)
Tower: An Open Multilingual Large Language Model for Translation-Related Tasks (arXiv 2024)
CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence in Korean (LREC-COLING2024)
Latxa: An Open Language Model and Evaluation Suite for Basque (ACL2024)
HyperCLOVA X Technical Report (arXiv 2024)
Sailor: Open Language Models for South-East Asia (arXiv 2024)
Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities (arXiv 2024)
Aya 23: Open Weight Releases to Further Multilingual Progress (arXiv 2024)
Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark (ACL2024)
LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs (arXiv 2024)
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages (arXiv 2024)
EXAONE 3.0 7.8B Instruction Tuned Language Model (arXiv 2024)
EuroLLM: Multilingual Language Models for Europe (arXiv 2024)
Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs (arXiv 2024)
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge (arXiv 2024)
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation (ACL2025)
Marco-LLM: Bridging Languages via Massive Multilingual Training for Cross-Lingual Enhancement (arXiv 2024)
Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier (arXiv 2024)
EXAONE 3.5: Series of Large Language Models for Real-world Use Cases (arXiv 2024)
Understand, Solve and Translate: Bridging the Multilingual Mathematical Reasoning Gap (arXiv 2025)
Kanana: Compute-efficient Bilingual Language Models (arXiv 2025)
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation (EMNLP2025)
EXAONE Deep: Reasoning Enhanced Language Models (arXiv 2025)
SEA-LION: Southeast Asian Languages in One Network (AACL2025)
Trillion 7B Technical Report (arXiv 2025)
Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs (arXiv 2025)
HyperCLOVA X THINK Technical Report (arXiv 2025)
EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes (arXiv 2025)
T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground (arXiv 2025)
K-EXAONE Technical Report (arXiv 2026)
Solar Open Technical Report (arXiv 2026)
EXAONE 4.5 Technical Report (arXiv 2026)
K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts (arXiv 2026)
Motif 3: Technical Report (arXiv 2026)

Other than English models

Domain specific

Multi-modal

Model compression

LLM

Reasoning and Chain of Thought

The Impact of Reasoning Step Length on Large Language Models (ACL2024 Findings)
Self-Rewarding Language Models (ICML2024)
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models [github] (arXiv 2024)
Chain-of-Thought Reasoning Without Prompting (NeurIPS2024)
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking (arXiv 2024)
AlphaMath Almost Zero: Process Supervision without Process (NeurIPS2024)
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search (NeurIPS2024)
Improve Mathematical Reasoning in Language Models by Automated Process Supervision (arXiv 2024)
Recursive Introspection: Teaching Language Model Agents How to Self-Improve (arXiv 2024)
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling (arXiv 2024)
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (arXiv 2024)
Generative Verifiers: Reward Modeling as Next-Token Prediction (ICLR2025)
Training Language Models to Self-Correct via Reinforcement Learning (arXiv 2024)
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions (arXiv 2024)
Free Process Rewards without Process Labels (arXiv 2024)
Training Large Language Models to Reason in a Continuous Latent Space [github] (COLM2025)
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking (arXiv 2025)
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models (arXiv 2025)
s1: Simple test-time scaling [github] (EMNLP2025)
Process Reinforcement through Implicit Rewards [github] (arXiv 2025)
Demystifying Long Chain-of-Thought Reasoning in LLMs (arXiv 2025)
LIMO: Less is More for Reasoning (COLM2025)
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling (arXiv 2025)
LIMR: Less is More for RL Scaling (arXiv 2025)
Chain of Draft: Thinking Faster by Writing Less (arXiv 2025)
L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning (COLM2025)
DAPO: An Open-Source LLM Reinforcement Learning System at Scale (arXiv 2025)
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models (TMLR)
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild (COLM2025)
Understanding R1-Zero-Like Training: A Critical Perspective (arXiv 2025)
A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? (arXiv 2025)
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model (arXiv 2025)
Sleep-time Compute: Beyond Inference Scaling at Test-time (arXiv 2025)
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? (NeurIPS2025)
TTRL: Test-Time Reinforcement Learning (arXiv 2025)
Reinforcement Learning for Reasoning in Large Language Models with One Training Example (arXiv 2025)
Absolute Zero: Reinforced Self-play Reasoning with Zero Data (arXiv 2025)
Reasoning Models Don't Always Say What They Think (arXiv 2025)
Reinforcement Learning Finetunes Small Subnetworks in Large Language Models (NeurIPS2025)
AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning (arXiv 2025)
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models (arXiv 2025)
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning (NeurIPS2025)
Reinforcement Pre-Training (arXiv 2025)
Self-Adapting Language Models (arXiv 2025)
Spurious Rewards: Rethinking Training Signals in RLVR (arXiv 2025)
Inverse Scaling in Test-Time Compute (TMLR)
DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning (arXiv 2025)
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning (arXiv 2025)
Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving (arXiv 2025)
Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models (arXiv 2025)
Universal Reasoning Model (arXiv 2025)
When Reasoning Meets Its Laws (arXiv 2025)
PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning (arXiv 2026)
The Molecular Structure of Thought: Mapping the Topology of Long Chain-of-Thought Reasoning (arXiv 2026)
Agentic Reasoning for Large Language Models (arXiv 2026)
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability (arXiv 2026)
Reinforcement Learning via Self-Distillation (arXiv 2026)
Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning (arXiv 2026)
No Global Plan in Chain-of-Thought: Uncover the Latent Planning Horizon of LLMs (arXiv 2026)
Does Your Reasoning Model Implicitly Know When to Stop Thinking? (arXiv 2026)
Experiential Reinforcement Learning (arXiv 2026)
How Far Can Unsupervised RLVR Scale LLM Training? (arXiv 2026)
Efficient Reasoning with Balanced Thinking (arXiv 2026)
Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs? (arXiv 2026)
Rethinking Generalization in Reasoning SFT: A Conditional Analysis on Optimization, Data, and Model Capability (arXiv 2026)
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe (arXiv 2026)
Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling (arXiv 2026)
Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs (arXiv 2026)
Weak-to-Strong Generalization via Direct On-Policy Distillation (arXiv 2026)
From RLVR to RLSVR: Task Transformation Induces Self-Verifiable Rewards for Open-Ended LLM Self-Improvement (arXiv 2026)
On-Policy Self-Distillation without Any Supervision (arXiv 2026)
Co-RL: Unsupervised Reasoning Emerges from Diverse Cohort in Multi-agent RL (arXiv 2026)

Alignment and RLHF

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback (arXiv 2022)
Constitutional AI: Harmlessness from AI Feedback (arXiv 2022)
RRHF: Rank Responses to Align Language Models with Human Feedback without tears (NeurIPS2023)
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment (TMLR)
Direct Preference Optimization: Your Language Model is Secretly a Reward Model (NeurIPS2023)
Secrets of RLHF in Large Language Models Part I: PPO (arXiv 2023)
RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback (ICML2024)
Statistical Rejection Sampling Improves Preference Optimization (ICLR2024)
Reward Model Ensembles Help Mitigate Overoptimization (ICLR2024)
A General Theoretical Paradigm to Understand Learning from Human Preferences (arXiv 2023)
Safe RLHF: Safe Reinforcement Learning from Human Feedback (arXiv 2023)
Zephyr: Direct Distillation of LM Alignment (arXiv 2023)
Controlled Decoding from Language Models (ICML2024)
Nash Learning from Human Feedback (arXiv 2023)
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision (arXiv 2023)
A Survey of Reinforcement Learning from Human Feedback (TMLR)
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation (ICML2024)
West-of-N: Synthetic Preferences for Self-Improving Reward Models (arXiv 2024)
WARM: On the Benefits of Weight Averaged Reward Models (arXiv 2024)
KTO: Model Alignment as Prospect Theoretic Optimization (ICML2024)
Aligner: Efficient Alignment by Learning to Correct (NeurIPS2024)
A Roadmap to Pluralistic Alignment (ICML2024)
ORPO: Monolithic Preference Optimization without Reference Model (EMNLP2024)
RewardBench: Evaluating Reward Models for Language Modeling (NAACL2025 Findings)
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study (ICML2024)
Token-level Direct Preference Optimization (arXiv 2024)
The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions (arXiv 2024)
Iterative Reasoning Preference Optimization (arXiv 2024)
SimPO: Simple Preference Optimization with a Reference-Free Reward (NeurIPS2024)
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling (arXiv 2024)
Safety Alignment Should Be Made More Than Just a Few Tokens Deep (arXiv 2024)
HybridFlow: A Flexible and Efficient RLHF Framework (arXiv 2024)
Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs (arXiv 2024)
Reinforcement Learning Enhanced LLMs: A Survey (arXiv 2024)
Alignment faking in large language models (arXiv 2024)
Deliberative Alignment: Reasoning Enables Safer Language Models (arXiv 2024)
Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs (ICML2025)
Auditing language models for hidden objectives (arXiv 2025)
Inference-Time Scaling for Generalist Reward Modeling (arXiv 2025)
RewardBench 2: Advancing Reward Model Evaluation (ICLR2026)
Stabilizing Reinforcement Learning with LLMs: Formulation and Practices (arXiv 2025)
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization (arXiv 2026)
Length-Unbiased Sequence Policy Optimization: Revealing and Controlling Response Length Variation in RLVR (arXiv 2026)
F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare (arXiv 2026)
VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training (arXiv 2026)
Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation (arXiv 2026)
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization (arXiv 2026)
Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex (arXiv 2026)
DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards (arXiv 2026)
The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning (arXiv 2026)
Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization (arXiv 2026)

Retrieval Augmented Generation

LLM Agents and Tool Use

Long Context and Efficient Architectures

Efficient Training Inference and Serving

Pretraining Data Scaling Laws and Model Merging

Scaling Data-Constrained Language Models (NeurIPS2023)
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only (NeurIPS2023)
TIES-Merging: Resolving Interference When Merging Models (NeurIPS2023)
An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning (arXiv 2023)
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch (ICML2024)
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws (ICML2024)
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research (ACL2024)
Datasets for Large Language Models: A Comprehensive Survey (arXiv 2024)
Simple and Scalable Strategies to Continually Pre-train Large Language Models (arXiv 2024)
Evolutionary Optimization of Model Merging Recipes (NatMachIntell2025)
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance (ICLR2025)
Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws (arXiv 2024)
DataComp-LM: In search of the next generation of training sets for language models (arXiv 2024)
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale (arXiv 2024)
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities (arXiv 2024)
Scaling Laws for Precision (arXiv 2024)
Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset (ACL2025)
Distillation Scaling Laws (ICML2025)
Ultra-FineWeb: Efficient Data Filtering and Verification for High-Quality LLM Training Data (arXiv 2025)
Parallel Scaling Law for Language Models (arXiv 2025)
The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text (arXiv 2025)
DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI (arXiv 2025)
Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs (arXiv 2026)
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration (arXiv 2026)
Less is Enough: Synthesizing Diverse Data in Feature Space of LLMs (arXiv 2026)
On Data Engineering for Scaling LLM Terminal Capabilities (arXiv 2026)
DataFlex: A Unified Data-Centric Dynamic Training Framework for Large Language Models (arXiv 2026)
Adam's Law: Textual Frequency Law on Large Language Models (arXiv 2026)
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora (arXiv 2026)
DataPrep-Bench: Benchmarking LLMs as Training Data Preparators (arXiv 2026)

Prompting and In Context Learning

Code LLM

RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation (EMNLP2023)
Teaching Large Language Models to Self-Debug (ICLR2024)
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation (NeurIPS2023)
StarCoder: may the source be with you! (arXiv 2023)
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems (ICLR2024)
WizardCoder: Empowering Code Large Language Models with Evol-Instruct (arXiv 2023)
Code Llama: Open Foundation Models for Code (arXiv 2023)
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion (NeurIPS2023)
Magicoder: Empowering Code Generation with OSS-Instruct (ICML2024)
Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models (arXiv 2023)
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution (ICML2024)
Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering (arXiv 2024)
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence (arXiv 2024)
StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback (arXiv 2024)
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement (ACL2024 Findings)
StarCoder 2 and The Stack v2: The Next Generation (arXiv 2024)
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code (arXiv 2024)
Granite Code Models: A Family of Open Foundation Models for Code Intelligence (arXiv 2024)
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data (arXiv 2024)
CodeGemma: Open Code Models Based on Gemma (arXiv 2024)
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence (arXiv 2024)
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions (ICLR2025)
Lean-STaR: Learning to Interleave Thinking and Proving (arXiv 2024)
DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search (arXiv 2024)
Qwen2.5-Coder Technical Report (arXiv 2024)
SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains? (arXiv 2024)
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models (ACL2025)
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings (arXiv 2025)
Competitive Programming with Large Reasoning Models (arXiv 2025)
SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering? (arXiv 2025)
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution (NeurIPS2025)
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding (COLM2025)
Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning (arXiv 2025)
SWE-smith: Scaling Data for Software Engineering Agents (arXiv 2025)
DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition (arXiv 2025)
Seed-Coder: Let the Code Model Curate Data for Itself (arXiv 2025)
LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming? (arXiv 2025)
From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence (arXiv 2025)
X-Coder: Advancing Competitive Programming with Fully Synthetic Tasks, Solutions, and Tests (arXiv 2026)
Advances and Frontiers of LLM-based Issue Resolution in Software Engineering: A Comprehensive Survey (arXiv 2026)
SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents (arXiv 2026)
daVinci-Dev: Agent-native Mid-training for Software Engineering (arXiv 2026)
SWE-Universe: Scale Real-World Verifiable Environments to Millions (arXiv 2026)
Qwen3-Coder-Next Technical Report (arXiv 2026)
BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing? (arXiv 2026)
InCoder-32B: Code Foundation Model for Industrial Scenarios (arXiv 2026)
LongCat-Flash-Prover: Advancing Native Formal Reasoning via Agentic Tool-Integrated Reinforcement Learning (arXiv 2026)
Embarrassingly Simple Self-Distillation Improves Code Generation (arXiv 2026)
GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning (arXiv 2026)
SWE-Explore: Benchmarking How Coding Agents Explore Repositories (arXiv 2026)
MaxProof: Scaling Mathematical Proof with Generative-Verifier RL and Population-Level Test-Time Scaling (arXiv 2026)
FastContext: Training Efficient Repository Explorer for Coding Agents (arXiv 2026)
The Verification Horizon: No Silver Bullet for Coding Agent Rewards (arXiv 2026)
Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models (arXiv 2026)
SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring (arXiv 2026)
SWE-bench Science: Can Coding Agents Resolve Engineering Tasks in Science? (arXiv 2026)

Evaluation and Benchmark

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena (NeurIPS2023)
A Survey on Evaluation of Large Language Models (arXiv 2023)
Time Travel in LLMs: Tracing Data Contamination in Large Language Models (ICLR2024)
GPQA: A Graduate-Level Google-Proof Q&A Benchmark (COLM2024)
OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems (ACL2024)
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference (ICML2024)
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators (COLM2024)
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark (NeurIPS2024)
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline (arXiv 2024)
LiveBench: A Challenging, Contamination-Limited LLM Benchmark (ICLR2025)
Measuring short-form factuality in large language models (arXiv 2024)
FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI (arXiv 2024)
Humanity's Last Exam (arXiv 2025)
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines (arXiv 2025)
BIG-Bench Extra Hard (ACL2025)
Measuring AI Ability to Complete Long Software Tasks (NeurIPS2025)
The Leaderboard Illusion (arXiv 2025)
HealthBench: Evaluating Large Language Models Towards Improved Human Health (arXiv 2025)
ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems (arXiv 2025)
DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle (arXiv 2025)
OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions (arXiv 2026)
GENIUS: Generative Fluid Intelligence Evaluation Suite (arXiv 2026)
RubricBench: Aligning Model-Generated Rubrics with Human Standards (arXiv 2026)
OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language World Models (arXiv 2026)
MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models (arXiv 2026)
MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations (arXiv 2026)
ASI-Bench: At the Dawn of Artificial Superintelligence (arXiv 2026)

Safety Hallucination and Interpretability

A Watermark for Large Language Models (ICML2023)
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature (ICML2023)
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (arXiv 2023)
SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models (EMNLP2023)
Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting (NeurIPS2023)
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models (EMNLP2023)
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation (EMNLP2023)
Jailbroken: How Does LLM Safety Training Fail? (NeurIPS2023)
Universal and Transferable Adversarial Attacks on Aligned Language Models (arXiv 2023)
Studying Large Language Model Generalization with Influence Functions (arXiv 2023)
SafetyBench: Evaluating the Safety of Large Language Models (ACL2024)
Language Models Represent Space and Time (ICLR2024)
Jailbreaking Black Box Large Language Models in Twenty Queries (arXiv 2023)
Towards Understanding Sycophancy in Language Models (ICLR2024)
Knowledge Editing for Large Language Models: A Survey (arXiv 2023)
A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions (TOIS)
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically (NeurIPS2024)
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training (arXiv 2024)
Security and Privacy Challenges of Large Language Models: A Survey (arXiv 2024)
Long-form factuality in large language models (NeurIPS2024)
The Geometry of Categorical and Hierarchical Concepts in Large Language Models (ICLR2025)
Scaling and evaluating sparse autoencoders (arXiv 2024)
Refusal in Language Models Is Mediated by a Single Direction (arXiv 2024)
Transcoders Find Interpretable LLM Feature Circuits (NeurIPS2024)
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps (EMNLP2024)
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2 (arXiv 2024)
Open Problems in Mechanistic Interpretability (arXiv 2025)
Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming (arXiv 2025)
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing (arXiv 2025)
Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation (arXiv 2025)
Defeating Prompt Injections by Design (arXiv 2025)
Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety (arXiv 2025)
Subliminal Learning: Language models transmit behavioral traits via hidden signals in data (arXiv 2025)
Persona Vectors: Monitoring and Controlling Character Traits in Language Models (arXiv 2025)
Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits (arXiv 2025)
Probabilistic Guarantees for Reducing Contextual Hallucinations in LLMs (arXiv 2026)
AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security (arXiv 2026)
Spider-Sense: Intrinsic Risk Sensing for Efficient Agent Defense with Hierarchical Adaptive Screening (arXiv 2026)
Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines? (arXiv 2026)
Thinking in Uncertainty: Mitigating Hallucinations in MLRMs with Latent Entropy-Aware Decoding (arXiv 2026)
Alignment Makes Language Models Normative, Not Descriptive (arXiv 2026)
Emergent Social Intelligence Risks in Generative Multi-Agent Systems (arXiv 2026)
Agentic Abstention: Do Agents Know When to Stop Instead of Act? (arXiv 2026)
AISPA: User-Centric System Prompt Auditing for Large Language Model Applications (arXiv 2026)
OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution (arXiv 2026)
The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads (arXiv 2026)
Stealing Reasoning Traces from Proprietary LLM APIs (arXiv 2026)

Misc

Author

ChangWookJun / @changwookjun ([email protected])

Rendered by GitHub from the current README

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changwookjun
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Quality score

Would you bet a product on this? Bounded 0–100 and slow moving.

56/10056

Maintenance: 90%; How recently the default branch was pushed to
Releases: 25%; Recency and cadence of tagged releases
Community: 5%; Contributor breadth and bus factor
Issue backlog: 100%; Open issues measured against the size of the audience
Documentation: 100%; README depth, plus a homepage and topics
Licensing: 0%; How freely the code can be adopted

What to know before adopting

No tagged releases
No license — all rights reserved by default, not safe to reuse
No licence file — default copyright applies, all rights reserved.

Categories

Foundation Modelsprimary80%
matched fp:fe04788522e8477d, topic:transformer, topic:language-model
NLP & Text Processing48%
matched fp:fe04788522e8477d, topic:nlp, readme:natural language processing, readme:text classification

Details

Created: 7 years ago
Last push: 26 days ago
Last release: none
Release tag: —
Releases in the last year: 0
Default branch: master
Size: 564 KB
Owner type: User
Owner location: Korea
Discovered via: topic:transformer
First indexed: 2 months ago
Last synced: 4 days ago