1 citations · 1 across the 7 of their papers we have counts for
10 papers
A Causal Perspective for Enhancing Jailbreak Attack and Defense
Licheng Pan, Yunsheng Lu, Jiexi Liu +5
Uncovering the mechanisms behind "jailbreaks" in large language models (LLMs) is crucial for enhancing their safety and reliability, yet these mechanisms remain poorly understood.…
UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters
Yongkun Du, Zhineng Chen, Yazhen Xie +6
Text and formulas constitute the core informational components of many documents. Accurately and efficiently recognizing both is crucial for developing robust and generalizable doc…
ChineseVideoBench: Benchmarking Multi-modal Large Models for Chinese Video Question Answering
Yuxiang Nie, Han Wang, Yongjie Ye +15
This paper introduces ChineseVideoBench, a pioneering benchmark specifically designed for evaluating Multimodal Large Language Models (MLLMs) in Chinese Video Question Answering. T…
From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models
Ziyan Wang, Enmao Diao, Qi Le +6
Structured pruning is a practical approach to deploying large language models (LLMs) efficiently, as it yields compact, hardware-friendly architectures. However, the dominant local…
Benchmarking Vision-Language Models on Chinese Ancient Documents: From OCR to Knowledge Reasoning
Haiyang Yu, Yuchuan Wu, Fan Shi +18
Chinese ancient documents, invaluable carriers of millennia of Chinese history and culture, hold rich knowledge across diverse fields but face challenges in digitization and unders…
GPU-Accelerated Belief Propagation for Program Analysis
Haoyu Feng, Xin Zhang
Belief Propagation (BP) is a widely used approximate inference algorithm in probabilistic graphical models (PGMs), but is computationally expensive when applied to large-scale prog…
Post-Completion Learning for Language Models
Xiang Fei, Siqi Wang, Shu Wei +5
Current language model training paradigms typically terminate learning upon reaching the end-of-sequence (<eos>) token, overlooking the potential learning opportunities in the post…
MEML-GRPO: Heterogeneous Multi-Expert Mutual Learning for RLVR Advancement
Weitao Jia, Jinghui Lu, Haiyang Yu +17
Recent advances demonstrate that reinforcement learning with verifiable rewards (RLVR) significantly enhances the reasoning capabilities of large language models (LLMs). However, s…
MCP-Zero: Active Tool Discovery for Autonomous LLM Agents
Xiang Fei, Xiawu Zheng, Hao Feng
True intelligence requires active capability acquisition, yet current LLM agents inject pre-defined tool schemas into prompts, reducing models to passive selectors and falling shor…
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
MiniMax, :, Aili Chen +125
We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE) architecture combin…