3 papers
cs.CL2026
Think-Probe-Respond: Improving Large Language Models as Judges of Research Idea Novelty
Tim Schopf, Tobias Schreieder, Akiko Aizawa
Automated novelty judgment can accelerate scientific discovery by enabling efficient evaluation, refinement, and comparison of research ideas. While large language models are incre…
cs.CL2026
Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs
Yihua Zhu, Qianying Liu, Jiaxin Wang +5
Autoregressive LLMs perform well on relational tasks that require linking entities via relational words (e.g., father/son, friend), but it is unclear whether they learn the logical…
cs.CL2025
Beyond Chains: Bridging Large Language Models and Knowledge Bases in Complex Question Answering
Yihua Zhu, Qianying Liu, Akiko Aizawa +1
Knowledge Base Question Answering (KBQA) aims to answer natural language questions using structured knowledge from KBs. While LLM-only approaches offer generalization, they suffer…