5 papers · 1 filter
Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR
Boyan Li, Bingsen Chen, Chenghao Yang +3
Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasoning LLMs. Prior work uses OPD's…
Small Language Models as Judges for Rubric-Based Reinforcement Learning
Fengyu Xie, Yilun Zhao, Bingsen Chen +2
Rubric-based reinforcement learning extends RL beyond tasks with exact answers or rule-based verifiers by scoring responses against instance-specific criteria. However, this makes…
Beyond Single-shot Writing: Deep Research Agents are Unreliable at Multi-turn Report Revision
Bingsen Chen, Boyan Li, Ping Nie +3
Existing benchmarks for Deep Research Agents (DRAs) treat report generation as a single-shot writing task, which fundamentally diverges from how human researchers iteratively draft…
Inter-Passage Verification for Multi-evidence Multi-answer QA
Bingsen Chen, Shengjie Wang, Xi Ye +1
Multi-answer question answering (QA), where questions can have many valid answers, presents a significant challenge for existing retrieval-augmented generation-based QA systems, as…
Arithmetic Reasoning with LLM: Prolog Generation & Permutation
Xiaocheng Yang, Bingsen Chen, Yik-Cheung Tam
Instructing large language models (LLMs) to solve elementary school math problems has shown great success using Chain of Thought (CoT). However, the CoT approach relies on an LLM t…