3 papers
cs.CL2025
Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks
Xinxi Lyu, Michael Duan, Rulin Shao +2
Retrieval-augmented Generation (RAG) has primarily been studied in limited settings, such as factoid question answering; more challenging, reasoning-intensive benchmarks have seen…
cs.CL2024
HREF: Human Response-Guided Evaluation of Instruction Following in Language Models
Xinxi Lyu, Yizhong Wang, Hannaneh Hajishirzi +1
Evaluating the capability of Large Language Models (LLMs) in following instructions has heavily relied on a powerful LLM as the judge, introducing unresolved biases that deviate th…
cs.CL2024
Tulu 3: Pushing Frontiers in Open Language Model Post-Training
Nathan Lambert, Jacob Morrison, Valentina Pyatkin +20
Language model post-training is applied to refine behaviors and unlock new skills across a wide range of recent language models, but open recipes for applying these techniques lag…