25 citations · 36 across the 19 of their papers we have counts for
6 papers · 1 filter
AgentSpec: Speculative Decoding for Batch Inference of LLM Agents
Xin Wang, Ziming Miao, Yi Zhu +4
Large language model (LLM)-based agent applications often incur high response time. Speculative decoding is a promising solution to improve the inference efficiency of LLM agents w…
Dynamic Linear Attention
Xin Wang, Hui Shen, Boyuan Zheng +7
The scalability of Large Language Models (LLMs) to long contexts is fundamentally constrained by the quadratic complexity of standard attention, motivating the adoption of linear a…
Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS
Alex ZH Dou, Zhongwei Wan, Dongfei Cui +6
Test-time scaling has emerged as a promising paradigm in language modeling, leveraging additional computational resources at inference time to enhance model performance. In this wo…
SRPO: Enhancing Multimodal LLM Reasoning via Reflection-Aware Reinforcement Learning
Zhongwei Wan, Zhihao Dou, Che Liu +11
Multimodal large language models (MLLMs) have shown promising capabilities in reasoning tasks, yet still struggle with complex problems requiring explicit self-reflection and self-…
SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compression
Xin Wang, Samiul Alam, Zhongwei Wan +2
Despite significant advancements, the practical deployment of Large Language Models (LLMs) is often hampered by their immense sizes, highlighting the need for effective compression…
MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference
Zhongwei Wan, Hui Shen, Xin Wang +3
Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-video modalities, demand substantial resources as their multimodal Key-Value (KV) ca…