5 papers
What Makes a Good Semantic ID for Generative Recommendation? A Reproducibility Study
Yufei Chen, Junchen Fu, Jujia Zhao +2
Generative recommendation has emerged as an active research direction, where items are commonly represented by semantic IDs (SIDs): discrete codes generated token by token. Despite…
Closing the Indexing-Decoding Gap in Multimodal Generative Retrieval via Prefix Retention Optimization
Yufei Chen, Zihan Wang, Yubao Tang +3
Multimodal generative retrieval formulates multimodal retrieval as discrete identifier generation, eliminating the need for explicit similarity search over external embeddings. Exi…
Seeing Before Agreeing: Aligning Multi-Agent Consensus with Visual Evidence
Yuhan Wang, Shuochen Chang, Yalin Feng +8
Vision-language models (VLMs) have achieved strong performance on visual question answering (VQA). To mitigate individual hallucinations and blind spots, aggregating diverse perspe…
LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Meituan LongCat Team, Bin Xiao, Chao Wang +86
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…
BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF
Kaiwen Duan, Hongwei Yao, Yufei Chen +4
Reinforcement Learning from Human Feedback (RLHF) is crucial for aligning text-to-image (T2I) models with human preferences. However, RLHF's feedback mechanism also opens new pathw…