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20222025
most citedDo Large Language Models Know What They Don't Know?

7 citations · 24 across the 25 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.AI2024

OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis

Qiushi Sun, Kanzhi Cheng, Zichen Ding +12

Graphical User Interface (GUI) agents powered by Vision-Language Models (VLMs) have demonstrated human-like computer control capability. Despite their utility in advancing digital…

cs.CL2024

OS-ATLAS: A Foundation Action Model for Generalist GUI Agents

Zhiyong Wu, Zhenyu Wu, Fangzhi Xu +8

Existing efforts in building GUI agents heavily rely on the availability of robust commercial Vision-Language Models (VLMs) such as GPT-4o and GeminiProVision. Practitioners are of…

cs.AI2024

AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant

Chengyou Jia, Minnan Luo, Zhuohang Dang +5

Digital agents capable of automating complex computer tasks have attracted considerable attention due to their immense potential to enhance human-computer interaction. However, exi…

cs.CL2024

Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis

Jianxiang Yu, Zichen Ding, Jiaqi Tan +10

In recent years, the rapid increase in scientific papers has overwhelmed traditional review mechanisms, resulting in varying quality of publications. Although existing methods have…

cs.CL2024★ 1 cited

Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models

Fangzhi Xu, Qiushi Sun, Kanzhi Cheng +3

One of the primary driving forces contributing to the superior performance of Large Language Models (LLMs) is the extensive availability of human-annotated natural language data, w…

cs.CL2024★ 1 cited

Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models

Zhangyue Yin, Qiushi Sun, Qipeng Guo +9

Recent advancements in Chain-of-Thought prompting have facilitated significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks. Current research enhances…

cs.HC2024★ 1 cited

SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents

Kanzhi Cheng, Qiushi Sun, Yougang Chu +4

Graphical User Interface (GUI) agents are designed to automate complex tasks on digital devices, such as smartphones and desktops. Most existing GUI agents interact with the enviro…

cs.CL2024★ 1 cited

KS-Lottery: Finding Certified Lottery Tickets for Multilingual Language Models

Fei Yuan, Chang Ma, Shuai Yuan +2

The lottery ticket hypothesis posits the existence of ``winning tickets'' within a randomly initialized neural network. Do winning tickets exist for LLMs in fine-tuning scenarios?…