2 citations · 3 across the 6 of their papers we have counts for
7 papers
LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
Xiang Long, Li Du, Yilong Xu +11
OpenClaw-style personal assistants extend LLM agents from isolated tool use to open-ended, stateful, and personalized software environments. Evaluating these assistants is fundamen…
CD-PIM: A High-Bandwidth and Compute-Efficient LPDDR5-Based PIM for Low-Batch LLM Acceleration on Edge-Device
Ye Lin, Chao Fang, Xiaoyong Song +4
Edge deployment of low-batch large language models (LLMs) faces critical memory bandwidth bottlenecks when executing memory-intensive general matrix-vector multiplications (GEMV) o…
Towards Compositional Generalization of LLMs via Skill Taxonomy Guided Data Synthesis
Yifan Wei, Li Du, Xiaoyan Yu +2
Large Language Models (LLMs) and agent-based systems often struggle with compositional generalization due to a data bottleneck in which complex skill combinations follow a long-tai…
Encyclo-K: Evaluating LLMs with Dynamically Composed Knowledge Statements
Yiming Liang, Yizhi Li, Yantao Du +14
Benchmarks play a crucial role in tracking the rapid advancement of large language models (LLMs) and identifying their capability boundaries. However, existing benchmarks predomina…
AutoTIR: Autonomous Tools Integrated Reasoning via Reinforcement Learning
Yifan Wei, Xiaoyan Yu, Yixuan Weng +3
Large Language Models (LLMs), when enhanced through reasoning-oriented post-training, evolve into powerful Large Reasoning Models (LRMs). Tool-Integrated Reasoning (TIR) further ex…
Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
Yifan Wei, Xiaoyan Yu, Tengfei Pan +2
Large language models (LLMs) have achieved unprecedented performance by leveraging vast pretraining corpora, yet their performance remains suboptimal in knowledge-intensive domains…
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang +2
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid…