1 citations · 1 across the 4 of their papers we have counts for
6 papers
Enhancing Image Quality Assessment Ability of LMMs via Retrieval-Augmented Generation
Kang Fu, Huiyu Duan, Zicheng Zhang +5
Large Multimodal Models (LMMs) have recently shown remarkable promise in low-level visual perception tasks, particularly in Image Quality Assessment (IQA), demonstrating strong zer…
CoDA: A Context-Decoupled Hierarchical Agent with Reinforcement Learning
Xuanzhang Liu, Jianglun Feng, Zhuoran Zhuang +7
Large Language Model (LLM) agents trained with reinforcement learning (RL) show great promise for solving complex, multi-step tasks. However, their performance is often crippled by…
InconVAD: A Two-Stage Dual-Tower Framework for Multimodal Emotion Inconsistency Detection
Zongyi Li, Junchuan Zhao, Francis Bu Sung Lee +1
Detecting emotional inconsistency across modalities is a key challenge in affective computing, as speech and text often convey conflicting cues. Existing approaches generally rely…
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought
Tencent Hunyuan Team, Ao Liu, Botong Zhou +248
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…
Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond
Lin Kyi, Amruta Mahuli, M. Six Silberman +3
Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these a…
Deep Reinforcement Learning for Sponsored Search Real-time Bidding
Jun Zhao, Guang Qiu, Ziyu Guan +2
Bidding optimization is one of the most critical problems in online advertising. Sponsored search (SS) auction, due to the randomness of user query behavior and platform nature, us…