5 papers · 1 filter
Causal Decoding for Hallucination-Resistant Multimodal Large Language Models
Shiwei Tan, Hengyi Wang, Weiyi Qin +3
Multimodal Large Language Models (MLLMs) deliver detailed responses on vision-language tasks, yet remain susceptible to object hallucination (introducing objects not present in the…
Taming Latency-Memory Trade-Off in MoE-Based LLM Serving via Fine-Grained Expert Offloading
Hanfei Yu, Xingqi Cui, Hong Zhang +1
Large Language Models (LLMs) have gained immense success in revolutionizing various applications, including content generation, search and recommendation, and AI-assisted operation…
Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models
Hengyi Wang, Haizhou Shi, Shiwei Tan +6
Multimodal Large Language Models (MLLMs) have shown significant promise in various applications, leading to broad interest from researchers and practitioners alike. However, a comp…
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models
Hengyi Wang, Shiwei Tan, Hao Wang
Vision transformers (ViTs) have emerged as a significant area of focus, particularly for their capacity to be jointly trained with large language models and to serve as robust visi…
Variational Language Concepts for Interpreting Foundation Language Models
Hengyi Wang, Shiwei Tan, Zhiqing Hong +2
Foundation Language Models (FLMs) such as BERT and its variants have achieved remarkable success in natural language processing. To date, the interpretability of FLMs has primarily…