6 papers
Diffusion Language Models Know the Answer Before Decoding
Pengxiang Li, Yefan Zhou, Dilxat Muhtar +5
Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and flexible token orders. However, the…
AdaptMMBench: Benchmarking Adaptive Multimodal Reasoning for Mode Selection and Reasoning Process
Xintong Zhang, Xiaowen Zhang, Jingrong Wu +8
Adaptive multimodal reasoning has emerged as a promising frontier in Vision-Language Models (VLMs), aiming to dynamically modulate between tool-augmented visual reasoning and text…
CrossLMM: Decoupling Long Video Sequences from LMMs via Dual Cross-Attention Mechanisms
Shilin Yan, Jiaming Han, Joey Tsai +5
The advent of Large Multimodal Models (LMMs) has significantly enhanced Large Language Models (LLMs) to process and interpret diverse data modalities (e.g., image and video). Howev…
Jarvis: Towards Personalized AI Assistant via Personal KV-Cache Retrieval
Binxiao Xu, Junyu Feng, Shaolin Lu +5
The rapid development of Vision-language models (VLMs) enables open-ended perception and reasoning. Recent works have started to investigate how to adapt general-purpose VLMs into…
UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens
Ruichuan An, Sihan Yang, Renrui Zhang +10
Personalized models have demonstrated remarkable success in understanding and generating concepts provided by users. However, existing methods use separate concept tokens for under…
Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking
Pengxiang Li, Shilin Yan, Joey Tsai +4
Classifier-Free Guidance (CFG) significantly enhances controllability in generative models by interpolating conditional and unconditional predictions. However, standard CFG often e…