activity
20232026
most citedOnline Analytic Exemplar-Free Continual Learning with Large Models for Imbalanced Autonomous Driving Task

14 citations · 22 across the 24 of their papers we have counts for

collaborators

25 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.CR2026

FreoStream:Enhancing Stream Guardrails via Future-Aware Reasoning and Safety-Aligned Optimization

Jianwei Wang, Guoyang Shen, Yanhong Wu +5

Stream guardrails enable token-level safety detection before full responses are generated. However, they often make overly conservative judgements and block those sensitive but saf…

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

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…