most citedFew-Shot Precise Event Spotting via Unified Multi-Entity Graph and Distillation

1 citations · 2 across the 5 of their papers we have counts for

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5 papers

cs.CV20251 cited

Few-Shot Precise Event Spotting via Unified Multi-Entity Graph and Distillation

Zhaoyu Liu, Kan Jiang, Murong Ma +3

Precise event spotting (PES) aims to recognize fine-grained events at exact moments and has become a key component of sports analytics. This task is particularly challenging due to…

cs.SE2025

PAT-Agent: Autoformalization for Model Checking

Xinyue Zuo, Yifan Zhang, Hongshu Wang +4

Recent advances in large language models (LLMs) offer promising potential for automating formal methods. However, applying them to formal verification remains challenging due to th…

cs.CR2025

Adaptive Plan-Execute Framework for Smart Contract Security Auditing

Zhiyuan Wei, Jing Sun, Zijian Zhang +2

Large Language Models (LLMs) have shown great promise in code analysis and auditing; however, they still struggle with hallucinations and limited context-aware reasoning. We introd…

cs.CV20251 cited

FSet: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos

Zhaoyu Liu, Kan Jiang, Murong Ma +3

Analyzing Fast, Frequent, and Fine-grained (F) events presents a significant challenge in video analytics and multi-modal LLMs. Current methods struggle to identify events that…

cs.AI2024

The Fusion of Large Language Models and Formal Methods for Trustworthy AI Agents: A Roadmap

Yedi Zhang, Yufan Cai, Xinyue Zuo +9

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generat…