activity
20232026
most citedChimera: A Lossless Decoding Method for Accelerating Large Language Models Inference by Fusing all Tokens

1 citations · 1 across the 11 of their papers we have counts for

collaborators

22 papers

cs.CV2026

EgoSafe: A First-Person Mobile-Captured Benchmark for Visual Safety Understanding

Yuyun Chen, Tianao Li, TianQuan Feng +4

Reliable visual safety understanding in real-world scenarios demands more than just object recognition; it requires causal reasoning under epistemic uncertainty. While Large Vision…

cs.LG2025

MixKVQ: Query-Aware Mixed-Precision KV Cache Quantization for Long-Context Reasoning

Tao Zhang, Ziqian Zeng, Hao Peng +2

Long Chain-of-Thought (CoT) reasoning has significantly advanced the capabilities of Large Language Models (LLMs), but this progress is accompanied by substantial memory and latenc…

cs.CR2025

ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behavior

Weikai Lu, Ziqian Zeng, Kehua Zhang +5

Multimodal Large Language Models (MLLMs) are increasingly vulnerable to multimodal Indirect Prompt Injection (IPI) attacks, which embed malicious instructions in images, videos, or…

cs.CL2025

RCP-Merging: Merging Long Chain-of-Thought Models with Domain-Specific Models by Considering Reasoning Capability as Prior

Junyao Yang, Jianwei Wang, Huiping Zhuang +2

Large Language Models (LLMs) with long chain-of-thought (CoT) capability, termed Reasoning Models, demonstrate superior intricate problem-solving abilities through multi-step long…

cs.CL2025

SynAdapt: Learning Adaptive Reasoning in Large Language Models via Synthetic Continuous Chain-of-Thought

Jianwei Wang, Ziming Wu, Fuming Lai +2

While Chain-of-Thought (CoT) reasoning improves model performance, it incurs significant time costs due to the generation of discrete CoT tokens (DCoT). Continuous CoT (CCoT) offer…

cs.CL2025

Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints

Zhengdong Lu, Weikai Lu, Yiling Tao +6

Despite significant advances in Large Language Models (LLMs), planning tasks still present challenges for LLM-based agents. Existing planning methods face two key limitations: heav…