7 papers
Detecting Contextual Hallucinations in LLMs with Frequency-Aware Attention
Siya Qi, Yudong Chen, Runcong Zhao +6
Hallucination detection is critical for ensuring the reliability of large language models (LLMs) in context-based generation. Prior work has explored intrinsic signals available du…
SegMo: Segment-aligned Text to 3D Human Motion Generation
Bowen Dang, Lin Wu, Xiaohang Yang +2
Generating 3D human motions from textual descriptions is an important research problem with broad applications in video games, virtual reality, and augmented reality. Recent method…
KidsArtBench: Multi-Dimensional Children's Art Evaluation with Attribute-Aware MLLMs
Mingrui Ye, Chanjin Zheng, Zengyi Yu +4
Multimodal Large Language Models (MLLMs) show remarkable progress across many visual-language tasks; however, their capacity to evaluate artistic expression remains limited. Aesthe…
A Survey of Automatic Hallucination Evaluation on Natural Language Generation
Siya Qi, Lin Gui, Yulan He +1
The rapid advancement of Large Language Models (LLMs) has brought a pressing challenge: how to reliably assess hallucinations to guarantee model trustworthiness. Although Automatic…
Steer-MoE: Efficient Audio-Language Alignment with a Mixture-of-Experts Steering Module
Ruitao Feng, Bixi Zhang, Sheng Liang +1
Aligning pretrained audio encoders and Large Language Models (LLMs) offers a promising, parameter-efficient path to building powerful multimodal agents. However, existing methods o…
Evaluating LLMs' Assessment of Mixed-Context Hallucination Through the Lens of Summarization
Siya Qi, Rui Cao, Yulan He +1
With the rapid development of large language models (LLMs), LLM-as-a-judge has emerged as a widely adopted approach for text quality evaluation, including hallucination evaluation.…