5 citations · 13 across the 15 of their papers we have counts for
16 papers
Multi-Level Aware Preference Learning: Enhancing RLHF for Complex Multi-Instruction Tasks
Ruopei Sun, Jianfeng Cai, Jinhua Zhu +5
RLHF has emerged as a predominant approach for aligning artificial intelligence systems with human preferences, demonstrating exceptional and measurable efficacy in instruction fol…
Bias Fitting to Mitigate Length Bias of Reward Model in RLHF
Kangwen Zhao, Jianfeng Cai, Jinhua Zhu +5
Reinforcement Learning from Human Feedback (RLHF) relies on reward models to align large language models with human preferences. However, RLHF often suffers from reward hacking, wh…
Multi-Scale Invertible Neural Network for Wide-Range Variable-Rate Learned Image Compression
Hanyue Tu, Siqi Wu, Li Li +2
Autoencoder-based structures have dominated recent learned image compression methods. However, the inherent information loss associated with autoencoders limits their rate-distorti…
Disentangling Length Bias In Preference Learning Via Response-Conditioned Modeling
Jianfeng Cai, Jinhua Zhu, Ruopei Sun +4
Reinforcement Learning from Human Feedback (RLHF) has achieved considerable success in aligning large language models (LLMs) by modeling human preferences with a learnable reward m…
LaneTCA: Enhancing Video Lane Detection with Temporal Context Aggregation
Keyi Zhou, Li Li, Wengang Zhou +3
In video lane detection, there are rich temporal contexts among successive frames, which is under-explored in existing lane detectors. In this work, we propose LaneTCA to bridge th…
SwinShadow: Shifted Window for Ambiguous Adjacent Shadow Detection
Yonghui Wang, Shaokai Liu, Li Li +2
Shadow detection is a fundamental and challenging task in many computer vision applications. Intuitively, most shadows come from the occlusion of light by the object itself, result…