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20222026
most citedWizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

29 citations · 110 across the 38 of their papers we have counts for

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7 papers · 1 filter

cs.CL2025

GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents

Qianhui Wu, Kanzhi Cheng, Rui Yang +15

One of the principal challenges in building VLM-powered GUI agents is visual grounding, i.e., localizing the appropriate screen region for action execution based on both the visual…

cs.CL2024★ 1 cited

AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Mengkang Hu, Pu Zhao, Can Xu +5

Large Language Model-based agents have garnered significant attention and are becoming increasingly popular. Furthermore, planning ability is a crucial component of an LLM-based ag…

cs.CL2024★ 3 cited

Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Jun Liu, Chaoyun Zhang, Jiaxu Qian +6

Time series anomaly detection (TSAD) plays a crucial role in various industries by identifying atypical patterns that deviate from standard trends, thereby maintaining system integ…

cs.CL2024★ 2 cited

LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang +10

This paper focuses on task-agnostic prompt compression for better generalizability and efficiency. Considering the redundancy in natural language, existing approaches compress prom…

cs.CL2024★ 2 cited

Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments

Sitao Cheng, Ziyuan Zhuang, Yong Xu +9

Large Language Models (LLMs) have shown potential in reasoning over structured environments, e.g., knowledge graph and table. Such tasks typically require multi-hop reasoning, i.e.…

cs.CL2023★ 29 cited

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Haipeng Luo, Qingfeng Sun, Can Xu +8

Large language models (LLMs), such as GPT-4, have shown remarkable performance in natural language processing (NLP) tasks, including challenging mathematical reasoning. However, mo…

cs.CL2023★ 3 cited

Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering

Fangkai Yang, Pu Zhao, Zezhong Wang +6

Large Language Model (LLM) has gained popularity and achieved remarkable results in open-domain tasks, but its performance in real industrial domain-specific scenarios is average d…