2 citations · 4 across the 8 of their papers we have counts for
8 papers
HarnessBank: Semantic Gene-Bank Search with Gated Verification for Agent-Harness Self-Evolution
Xiaotian Luo, Dizhan Xue, Fengxingyu Wang +2
Large Language Models (LLMs) have enabled capable agents across diverse applications. Beyond the foundation model, the performance of an agent is governed by the surrounding agent…
SoMe: A Realistic Benchmark for LLM-based Social Media Agents
Dizhan Xue, Jing Cui, Shengsheng Qian +2
Intelligent agents powered by large language models (LLMs) have recently demonstrated impressive capabilities and gained increasing popularity on social media platforms. While LLM…
Short-video Propagation Influence Rating: A New Real-world Dataset and A New Large Graph Model
Dizhan Xue, Shengsheng Qian, Chuanrui Hu +1
Short-video platforms have gained immense popularity, captivating the interest of millions, if not billions, of users globally. Recently, researchers have highlighted the significa…
SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding
Zhenyu Yang, Yuhang Hu, Zemin Du +6
Despite the significant advancements of Large Vision-Language Models (LVLMs) on established benchmarks, there remains a notable gap in suitable evaluation regarding their applicabi…
From Linguistic Giants to Sensory Maestros: A Survey on Cross-Modal Reasoning with Large Language Models
Shengsheng Qian, Zuyi Zhou, Dizhan Xue +2
Cross-modal reasoning (CMR), the intricate process of synthesizing and drawing inferences across divergent sensory modalities, is increasingly recognized as a crucial capability in…
BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents
Yifei Wang, Dizhan Xue, Shengjie Zhang +1
With the prosperity of large language models (LLMs), powerful LLM-based intelligent agents have been developed to provide customized services with a set of user-defined tools. Stat…
Erasing Self-Supervised Learning Backdoor by Cluster Activation Masking
Shengsheng Qian, Dizhan Xue, Yifei Wang +3
Self-Supervised Learning (SSL) is an effective paradigm for learning representations from unlabeled data, such as text, images, and videos. However, researchers have recently found…
A Survey on Interpretable Cross-modal Reasoning
Dizhan Xue, Shengsheng Qian, Zuyi Zhou +1
In recent years, cross-modal reasoning (CMR), the process of understanding and reasoning across different modalities, has emerged as a pivotal area with applications spanning from…