3 papers
cs.HC2025
Multi-Hop Question Answering: When Can Humans Help, and Where do They Struggle?
Jinyan Su, Claire Cardie, Jennifer Healey
Multi-hop question answering is a challenging task for both large language models (LLMs) and humans, as it requires recognizing when multi-hop reasoning is needed, followed by read…
cs.CL2025
Thinking Fast and Right: Balancing Accuracy and Reasoning Length with Adaptive Rewards
Jinyan Su, Claire Cardie
Large language models (LLMs) have demonstrated strong reasoning abilities in mathematical tasks, often enhanced through reinforcement learning (RL). However, RL-trained models freq…
cs.LG2025
SAGE: A Framework of Precise Retrieval for RAG
Jintao Zhang, Guoliang Li, Jinyang Su
Retrieval-augmented generation (RAG) has demonstrated significant proficiency in conducting question-answering (QA) tasks within a specified corpus. Nonetheless, numerous failure i…