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20242026
most citedAgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System

10 citations · 24 across the 26 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

Jixuan Chen, Jiaxin Zhang, Qinyuan Ye +11

Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existing harness-model co-evolutio…

cs.CL2026

Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models

Liangwei Yang, Shiyu Wang, Haolin Chen +12

As large language models (LLMs) transition from research prototypes to real-world systems, customization has emerged as a central bottleneck. While text prompts can already customi…

cs.CL2026

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

Wei-Chieh Huang, Weizhi Zhang, Yueqing Liang +56

Research in artificial intelligence is shifting from model innovations and benchmark scores towards problem definition and rigorous real-world evaluation. As the field enters the "…

cs.CL2025

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models

Rithesh Murthy, Ming Zhu, Liangwei Yang +6

Large Language Models (LLMs) perform best with well-crafted prompts, yet prompt engineering remains manual, inconsistent, and inaccessible to non-experts. We introduce Promptomatix…

cs.CL2025

Entropy-Based Block Pruning for Efficient Large Language Models

Liangwei Yang, Yuhui Xu, Juntao Tan +5

As large language models continue to scale, their growing computational and storage demands pose significant challenges for real-world deployment. In this work, we investigate redu…

cs.CL2024★ 5 cited

xLAM: A Family of Large Action Models to Empower AI Agent Systems

Jianguo Zhang, Tian Lan, Ming Zhu +19

Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing speci…

cs.CL2024★ 2 cited

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets

Zuxin Liu, Thai Hoang, Jianguo Zhang +14

The advancement of function-calling agent models requires diverse, reliable, and high-quality datasets. This paper presents APIGen, an automated data generation pipeline designed t…

cs.CL2024★ 2 cited

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases

Rithesh Murthy, Liangwei Yang, Juntao Tan +15

The deployment of Large Language Models (LLMs) and Large Multimodal Models (LMMs) on mobile devices has gained significant attention due to the benefits of enhanced privacy, stabil…