1 citations · 1 across the 7 of their papers we have counts for
8 papers
SafeCoEvo: Co-Evolving Safety Harnesses and Guards for LLM Agents at Test-Time
Yu Cheng, Yongkang Hu, Shuaijie Ma +12
LLM agents deployed in real-world environments continually encounter new tasks and safety risks, while execution feedback typically becomes available only after each task is comple…
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD
Dongfang Li, Xiaodong Luo, Ruoyu Sun +62
Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pre…
Memory Intelligence Agent
Jingyang Qiao, Weicheng Meng, Yu Cheng +6
Deep research agents (DRAs) integrate LLM reasoning with external tools. Memory systems enable DRAs to leverage historical experiences, which are essential for efficient reasoning…
ORGEval: Graph-Theoretic Evaluation of LLMs in Optimization Modeling
Zhuohan Wang, Ziwei Zhu, Ziniu Li +8
Formulating optimization problems for industrial applications demands significant manual effort and domain expertise. While Large Language Models (LLMs) show promise in automating…
Exact Causal Attention with 10% Fewer Operations
Dmitry Rybin, Yushun Zhang, Ding Tian +2
We present Exact Causal Attention (ECA), a Strassen-style algorithm that computes exact Causal Attention using 10\% fewer operations. ECA improves a special class of matrix multipl…
Bridging Formal Language with Chain-of-Thought Reasoning to Geometry Problem Solving
Tianyun Yang, Yunwen Li, Ziniu Li +3
Large vision language models exhibit notable limitations on Geometry Problem Solving (GPS) because of their unreliable diagram interpretation and pure natural-language reasoning. A…
Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion
Jianqing Zhu, Huang Huang, Zhihang Lin +18
This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to st…
MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning
Yupeng Chen, Senmiao Wang, Yushun Zhang +5
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks. Typically, LLMs are first pre-trained on large corpora and subsequently fine-tu…