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1. Benchmarking Open-Ended Multi-Agent Coordination in Language Agents
   arXiv.org2026-06-06alphaXiv arXiv S2
2. DéjàQ: Open-Ended Evolution of Diverse, Learnable and Verifiable Problems
   arXiv.org2026-01-05alphaXiv arXiv S2
3. Check Your Work: Structured Checklist Feedback for Improving Large Language Models
   Annual Meeting of the Association for Computational Linguistics2026S2
4. ACRM: Multi-Agent Trajectory Learning for Automated Credit Risk Model Refreshing in Production
   Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)2026S2
5. Towards Uncovering How Large Language ModelsWork: An Interpretability Perspective
   SIGKDD Explorations2025-12-30S2
6. Imagined Autocurricula
   Neural Information Processing Systems2025-09-11alphaXiv arXiv S2
7. Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents
   arXiv.org2025-09-03alphaXiv arXiv S2
8. Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
   2025-06-23alphaXiv arXiv S2
9. LLM-First Search: Self-Guided Exploration of the Solution Space
   arXiv.org2025-06-05alphaXiv arXiv S2
10. D3PO: Preference-Based Alignment of Discrete Diffusion Models
    arXiv.org2025-03-11alphaXiv arXiv S2
11. Investigating Non-Transitivity in LLM-as-a-Judge
    International Conference on Machine Learning2025-02-19alphaXiv arXiv S2
12. InterFeedback: Unveiling Interactive Intelligence of Large Multimodal Models with Human Feedback
    Conference on Empirical Methods in Natural Language Processing2025S2
13. Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training
    arXiv.org2025S2
14. Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
    International Conference on Learning Representations2025S2
15. BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
    International Conference on Learning Representations2024-11-20alphaXiv arXiv S2
16. Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
    arXiv.org2024-11-19alphaXiv arXiv S2
17. TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation
    arXiv.org2024-10-04alphaXiv arXiv S2
18. Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
    International Conference on Learning Representations2024S2
19. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
    Neural Information Processing Systems2023S2
20. JaxMARL: Multi-Agent RL Environments in JAX
    arXiv.org2023S2
21. Graph Memory-based Editing for Large Language Models
    S2
22. Conference on Empirical Methods in Natural Language Processing Proceedings of the Fourth International Workshop on Natural Language Processing for Social Media Socialnlp@emnlp2016 Chairs' Welcome Identifying and Categorizing Disaster-related Tweets Why Do They Leave: Modeling Participation in Online
    S2
23. A Systematic Literature Review of Adapter-based Approaches to Knowledge-enhanced Language Models
    S2
24. On Reward Functions For Self-Improving Chain-of-Thought Reasoning Without Supervised Datasets (Abridged Version)
    S2