519 citations · 852 across the 15 of their papers we have counts for
5 papers · 1 filter
Training Reasoning Models to Generate Diverse Scientific Ideas
Manya Wadhwa, Pranav Narayanan Venkit, Hiroaki Hayashi +3
One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of this work optimizes the qua…
Agentic Self-Awareness: Aligning Knowing, Acting, and Holding
Qinglin Chen, Hiroaki Hayashi, Jiaxin Zhang +1
Frontier AI agents increasingly act in environments where seemingly solvable tasks may lack prerequisites, contain conflicting requirements, or reveal blockers only during executio…
Self-Retrospection Distillation: Turning Post-hoc Experiences into Prior Foresight
Haoxiang Zhang, Qinglin Chen, Hiroaki Hayashi +9
Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through scalar outcome rewards after interaction. For group-relative ob…
Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps
Jiaxin Zhang, Xiangyu Peng, Qinglin Chen +3
Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental consequences, leaving the agen…
Redesigning and Auditing Deep Research Writing for Faithful Reports
Hiroaki Hayashi, Pranav Narayanan Venkit, Prafulla Kumar Choubey +1
Rubric-based evaluations of deep-research (DR) systems often obscure fine-grained factual failures in generated reports. We introduce CLAIMPROBE, a claim-level audit that decompose…