2 citations · 2 across the 4 of their papers we have counts for
6 papers
PEAR: Phase Entropy Aware Reward for Efficient Reasoning
Chen Huang, Wei Lu, Wenxuan Zhang
Large Reasoning Models (LRMs) have achieved impressive performance on complex reasoning tasks by generating detailed chain-of-thought (CoT) explanations. However, these responses a…
MMR1: Enhancing Multimodal Reasoning with Variance-Aware Sampling and Open Resources
Sicong Leng, Jing Wang, Jiaxi Li +12
Large multimodal reasoning models have achieved rapid progress, but their advancement is constrained by two major limitations: the absence of open, large-scale, high-quality long c…
Through the Valley: Path to Effective Long CoT Training for Small Language Models
Renjie Luo, Jiaxi Li, Chen Huang +1
Long chain-of-thought (CoT) supervision has become a common strategy to enhance reasoning in language models. While effective for large models, we identify a phenomenon we call Lon…
From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition
Tianduo Wang, Lu Xu, Wei Lu +1
Recent advances in Automatic Speech Recognition (ASR) have been largely fueled by massive speech corpora. However, extending coverage to diverse languages with limited resources re…
Vidi: Large Multimodal Models for Video Understanding and Editing
Vidi Team, Celong Liu, Chia-Wen Kuo +20
Humans naturally share information with those they are connected to, and video has become one of the dominant mediums for communication and expression on the Internet. To support t…
Analyzable Chain-of-Musical-Thought Prompting for High-Fidelity Music Generation
Max W. Y. Lam, Yijin Xing, Weiya You +14
Autoregressive (AR) models have demonstrated impressive capabilities in generating high-fidelity music. However, the conventional next-token prediction paradigm in AR models does n…