4 citations · 4 across the 4 of their papers we have counts for
4 papers
NovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment
Guoqiang Zhang, Kexin Tan, Ming Zhang +12
Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchmarks assess novelty as a sing…
Faithfulness-QA: A Counterfactual Entity Substitution Dataset for Training Context-Faithful RAG Models
Li Ju, Junzhe Wang, Qi Zhang
Retrieval-Augmented Generation (RAG) models frequently produce answers grounded in parametric memory rather than the retrieved context, undermining the core promise of retrieval au…
OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment
Ming Zhang, Kexin Tan, Yueyuan Huang +20
Evaluating novelty is critical yet challenging in peer review, as reviewers must assess submissions against a vast, rapidly evolving literature. This report presents OpenNovelty, a…
WisPaper: Your AI Scholar Search Engine
Li Ju, Jun Zhao, Mingxu Chai +24
We present \textsc{WisPaper}, an end-to-end agent system that transforms how researchers discover, organize, and track academic literature. The system addresses two fundamental cha…