106 citations · 110 across the 13 of their papers we have counts for
13 papers
Can Retrievers Find the Same Paper from Different Aspects? A Multi-Aspect Full-Paper Scientific Retrieval Benchmark
Yiyang Wei, Fang Guo, Qiji Zhou +4
Scientific papers contain multiple searchable facets such as background, methods. However, many paper retrieval benchmarks merely evaluate individual query-paper relevance, while o…
Triospect: A Three-Dimensional Framework for Robust Statistical AI-Generated Text Detection Against Diverse Attacks
Guangsheng Bao, Lihua Rong, Yanbin Zhao +3
Existing AI-generated text detectors are vulnerable to attacks that manipulate textual characteristics. In this study, we propose a novel Triospect Detection Framework by using add…
AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists
Junshu Pan, Panzhong Lu, Yixuan Weng +5
Recent advances in artificial intelligence (AI) have accelerated the growth of both human-authored and AI-generated research outputs, placing increasing strain on traditional acade…
LAGO: Language-Guided Adaptive Object-Region Focus for Zero-Shot Visual-Text Alignment
Junyi Hu, Qiji Zhou, Lei Zhang +1
Zero-shot visual recognition often depends on localized parts, attributes, and textures that are diluted in global image representations. Existing training-free localized methods a…
ALLabel: Three-stage Active Learning for LLM-based Entity Recognition using Demonstration Retrieval
Zihan Chen, Lei Shi, Weize Wu +2
Many contemporary data-driven research efforts in the natural sciences, such as chemistry and materials science, require large-scale, high-performance entity recognition from scien…
Airalogy: AI-empowered universal data digitization for research automation
Zijie Yang, Qiji Zhou, Fang Guo +19
Research data are the foundation of Artificial Intelligence (AI)-driven science, yet current AI applications remain limited to a few fields with readily available, well-structured,…
Pre-DPO: Improving Data Utilization in Direct Preference Optimization Using a Guiding Reference Model
Junshu Pan, Wei Shen, Shulin Huang +2
Direct Preference Optimization (DPO) simplifies reinforcement learning from human feedback (RLHF) for large language models (LLMs) by directly optimizing human preferences without…
Reasoning is All You Need for Video Generalization: A Counterfactual Benchmark with Sub-question Evaluation
Qiji Zhou, Yifan Gong, Guangsheng Bao +5
Counterfactual reasoning is crucial for robust video understanding but remains underexplored in existing multimodal benchmarks. In this paper, we introduce \textbf{COVER} (\textbf{…
Decoupling Content and Expression: Two-Dimensional Detection of AI-Generated Text
Guangsheng Bao, Lihua Rong, Yanbin Zhao +2
The wide usage of LLMs raises critical requirements on detecting AI participation in texts. Existing studies investigate these detections in scattered contexts, leaving a systemati…
Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models
Qiji Zhou, Ruochen Zhou, Zike Hu +3
Recent advancements in Chain-of-Thought (CoT) and related rationale-based works have significantly improved the performance of Large Language Models (LLMs) in complex reasoning tas…
GLoRE: Evaluating Logical Reasoning of Large Language Models
Hanmeng liu, Zhiyang Teng, Ruoxi Ning +4
Large language models (LLMs) have shown significant general language understanding abilities. However, there has been a scarcity of attempts to assess the logical reasoning capacit…
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4
Hanmeng Liu, Ruoxi Ning, Zhiyang Teng +3
Harnessing logical reasoning ability is a comprehensive natural language understanding endeavor. With the release of Generative Pretrained Transformer 4 (GPT-4), highlighted as "ad…
LogiCoT: Logical Chain-of-Thought Instruction-Tuning
Hanmeng Liu, Zhiyang Teng, Leyang Cui +3
Generative Pre-trained Transformer 4 (GPT-4) demonstrates impressive chain-of-thought reasoning ability. Recent work on self-instruction tuning, such as Alpaca, has focused on enha…