38 citations · 90 across the 18 of their papers we have counts for
4 papers · 1 filter
Which Metrics Save the Most Human Annotation? Prediction-Powered Evaluation and Meta-Evaluation
Mingqi Gao, Anthony Sicilia, Weiyan Shi
Across various non-verifiable tasks, human evaluation is reliable but expensive, while automatic metrics are more scalable but often biased. Building on prediction-powered inferenc…
OmniReasoner: Thinking with Long Audio-Video via Native Tool Use
Yu Chen, Caorui Li, Ziyu Xiong +8
Long audio-video reasoning is difficult for omnimodal LLMs because the decisive evidence is often sparse, cross-modal, and too expensive to preserve with uniformly high-fidelity in…
Claim-Level Rubric Rewards for Video Caption Reinforcement Learning
Mingqi Gao, Hongyuan Dong, Yifei Chen +6
In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinforcement learning for dense vi…
Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe
Wenjin Hou, Shangpin Peng, Weinong Wang +13
On-policy distillation (OPD) has recently emerged as an effective post-training paradigm for consolidating the capabilities of specialized expert models into a single student model…