5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CL2025★ 5 cited
The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
Chenglei Si, Tatsunori Hashimoto, Diyi Yang
Large Language Models (LLMs) have shown promise in accelerating the scientific research pipeline. A key capability for this process is the ability to generate novel research ideas,…
cs.AI2025
Contextual Experience Replay for Self-Improvement of Language Agents
Yitao Liu, Chenglei Si, Karthik Narasimhan +1
Large language model (LLM) agents have been applied to sequential decision-making tasks such as web navigation, but without any environment-specific experiences, they often fail in…