Key papers

• SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model (2025)
  Loubna Ben Allal et al.
  6.58
• Rushes: A Human Preference Dataset for Pluralistic Alignment (2026)
  Michael Xu et al.
  5.01
• A Unified Moral-Value Dataset for Instruction Tuning (2026)
  Zhaohui Zeng et al.
  5.01
• Decision Protocols in Multi-Agent Large Language Model Conversations (2026)
  Lars Benedikt Kaesberg
  4.39
• Beyond Ideal Instruction: A Comprehensive Framework for Evaluating LLMs in Realistic Interactions (2026)
  Xuan Yang et al.
  4.33
• LLMs Are Already Good Tutors: Training-Free Prompt Optimization for Pedagogical Math Tutoring (2026)
  Unggi Lee et al.
  4.27
• QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL (2025)
  Cong Yu et al.
  3.10
• BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models (2025)
  Xu Huang et al.
  2.87
• Web-Shepherd: Advancing PRMs for Reinforcing Web Agents (2025)
  Hyungjoo Chae et al.
  2.82
• PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction (2026)
  Zhuoqun Li et al.
  2.00
• Parallelized Autoregressive Decoding for Omni-Modal Dense Video Captioning (2026)
  Wenzheng Zeng et al.
  2.00
• Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling (2026)
  Xiang Hu et al.
  2.00
• EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs (2026)
  Jewon Yeom et al.
  1.94
• dVoting: Fast Voting for dLLMs (2026)
  Sicheng Feng et al.
  1.94
• Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents (2026)
  Wenxuan Ding et al.
  1.94
• Learning to Commit: Generating Organic Pull Requests via Online Repository Memory (2026)
  Mo Li et al.
  1.94
• MoEITS: A Green AI approach for simplifying MoE-LLMs (2026)
  Luis Balderas et al.
  1.83
• Small is Beautiful: A Practical and Efficient Log Parsing Framework (2026)
  Minxing Wang et al.
  1.67
• EnvX: Agentize Everything with Agentic AI (2025)
  Linyao Chen et al.
  1.44
• NEFMind: Parameter-Efficient Fine-Tuning of Open-Source LLMs for Telecom APIs Automation (2025)
  Zainab Khan et al.
  1.39
• InferLog: Accelerating LLM Inference for Online Log Parsing via ICL-oriented Prefix Caching (2025)
  Yilun Wang and Pengfei Chen and Haiyu Huang and Zilong He and Gou Tan and Chuanfu Zhang and Jingkai He and Zibin Zheng
  1.33
• Step-Opt: Boosting Optimization Modeling in LLMs through Iterative Data Synthesis and Structured Validation (2025)
  Yang Wu et al.
  1.28
• Thunder-LLM: Efficiently Adapting LLMs to Korean with Minimal Resources (2025)
  Jinpyo Kim et al.
  1.28
• Linear-MoE: Linear Sequence Modeling Meets Mixture-of-Experts (2025)
  Weigao Sun et al.
  1.28
• PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines (2025)
  Reya Vir et al.
  1.28
• Technical Report: Full-Stack Fine-Tuning for the Q Programming Language (2025)
  Brendan R. Hogan et al.
  1.28
• Fast-dLLM v2: Efficient Block-Diffusion LLM (2025)
  Chengyue Wu et al.
  1.28
• Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling (2025)
  Hao Mark Chen et al.
  1.22
• ExTrans: Multilingual Deep Reasoning Translation via Exemplar-Enhanced Reinforcement Learning (2025)
  Jiaan Wang et al.
  1.22
• xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference (2025)
  Maximilian Beck et al.
  1.11
• ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario (2025)
  Lucen Zhong et al.
  1.00
• ELIT: Emory Language and Information Toolkit (2021)
  Han He and Liyan Xu and Jinho D. Choi
  —
• DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents (2021)
  Kunal Dahiya et al.
  —
• SGP-TOD: Building Task Bots Effortlessly via Schema-Guided LLM Prompting (2023)
  Xiaoying Zhang et al.
  —
• Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering (2023)
  Fangkai Yang et al.
  —
• LLMeBench: A Flexible Framework for Accelerating LLMs Benchmarking (2023)
  Fahim Dalvi et al.
  —
• CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning (2023)
  Yilun Liu et al.
  —
• Intelligent Virtual Assistants with LLM-based Process Automation (2023)
  Yanchu Guan et al.
  —
• Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs (2024)
  Yeonhong Park et al.
  —
• Hire a Linguist!: Learning Endangered Languages with In-Context Linguistic Descriptions (2024)
  Kexun Zhang et al.
  —
• LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training (2024)
  Tong Zhu et al.
  —
• Developing a Tutoring Dialog Dataset to Optimize LLMs for Educational Use (2024)
  Menna Fateen et al.
  —
• LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training (2024)
  Xiaoye Qu et al.
  —
• 7B Fully Open Source Moxin-LLM/VLM -- From Pretraining to GRPO-based Reinforcement Learning Enhancement (2024)
  Pu Zhao et al.
  —
• WEPO: Web Element Preference Optimization for LLM-based Web Navigation (2024)
  Jiarun Liu et al.
  —
• GMoE: Empowering LLMs Fine-Tuning via MoE Graph Collaboration (2024)
  Ting Bai et al.
  —
• PaLM 2 Technical Report (2023)
  Rohan Anil et al.
  —
• Mind2Web: Towards a Generalist Agent for the Web (2023)
  Xiang Deng et al.
  —
• TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT (2023)
  Liangyu Zha et al.
  —
• FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets (2023)
  Seonghyeon Ye et al.
  —
• Ziya2: Data-centric Learning is All LLMs Need (2023)
  Ruyi Gan et al.
  —
• Advancing LLM Reasoning Generalists with Preference Trees (2024)
  Lifan Yuan et al.
  —
• CodecLM: Aligning Language Models with Tailored Synthetic Data (2024)
  Zifeng Wang et al.
  —
• OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework (2024)
  Sachin Mehta et al.
  —
• Xwin-LM: Strong and Scalable Alignment Practice for LLMs (2024)
  Bolin Ni et al.
  —
• Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients (2024)
  Aashiq Muhamed et al.
  —
• Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training (2024)
  Youliang Yuan et al.
  —
• OpenDevin: An Open Platform for AI Software Developers as Generalist Agents (2024)
  Xingyao Wang et al.
  —
• MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions (2024)
  Yekun Chai et al.
  —
• LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models (2024)
  Zhengyi Wang et al.
  —