Search Results for author: Tianhang Zhang

Found 10 papers, 9 papers with code

ECon: On the Detection and Resolution of Evidence Conflicts

1 code implementation5 Oct 2024 Cheng Jiayang, Chunkit Chan, Qianqian Zhuang, Lin Qiu, Tianhang Zhang, Tengxiao Liu, Yangqiu Song, Yue Zhang, PengFei Liu, Zheng Zhang

The rise of large language models (LLMs) has significantly influenced the quality of information in decision-making systems, leading to the prevalence of AI-generated content and challenges in detecting misinformation and managing conflicting information, or "inter-evidence conflicts."

Decision Making Misinformation +1

RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation

1 code implementation15 Aug 2024 Dongyu Ru, Lin Qiu, Xiangkun Hu, Tianhang Zhang, Peng Shi, Shuaichen Chang, Cheng Jiayang, Cunxiang Wang, Shichao Sun, Huanyu Li, Zizhao Zhang, Binjie Wang, Jiarong Jiang, Tong He, Zhiguo Wang, PengFei Liu, Yue Zhang, Zheng Zhang

Despite Retrieval-Augmented Generation (RAG) showing promising capability in leveraging external knowledge, a comprehensive evaluation of RAG systems is still challenging due to the modular nature of RAG, evaluation of long-form responses and reliability of measurements.

RAG Retrieval

Attention Fusion Reverse Distillation for Multi-Lighting Image Anomaly Detection

no code implementations7 Jun 2024 Yiheng Zhang, Yunkang Cao, Tianhang Zhang, Weiming Shen

This study targets Multi-Lighting Image Anomaly Detection (MLIAD), where multiple lighting conditions are utilized to enhance imaging quality and anomaly detection performance.

Anomaly Detection

RepEval: Effective Text Evaluation with LLM Representation

1 code implementation30 Apr 2024 Shuqian Sheng, Yi Xu, Tianhang Zhang, Zanwei Shen, Luoyi Fu, Jiaxin Ding, Lei Zhou, Xiaoying Gan, Xinbing Wang, Chenghu Zhou

Besides, previous LLM-based metrics ignore the fact that, within the space of LLM representations, there exist direction vectors that indicate the estimation of text quality.

SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully

2 code implementations11 Jan 2024 Jushi Kai, Tianhang Zhang, Hai Hu, Zhouhan Lin

Therefore, we propose to ''highlight'' the factual information by selecting the tokens with the lowest probabilities and concatenating them to the original context, thus forcing the model to repeatedly read and hesitate on these tokens before generation.

Hallucination Text Generation

Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus

1 code implementation22 Nov 2023 Tianhang Zhang, Lin Qiu, Qipeng Guo, Cheng Deng, Yue Zhang, Zheng Zhang, Chenghu Zhou, Xinbing Wang, Luoyi Fu

Large Language Models (LLMs) have gained significant popularity for their impressive performance across diverse fields.

Hallucination Retrieval

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