1.1k citations · 1.1k across the 13 of their papers we have counts for
14 papers
SurveyReview: A Reviewer-Aligned Benchmark for Survey Evaluators
Yuheng Zhang, Yuanchun Wang, Fanjin Zhang +4
The rapid advancement of large language models has transformed survey writing from a months-long manual effort into an automated process. As generation scales, reliable evaluation…
AISE-Bench: A Full-Cycle Curated Benchmark for Information Seeking on Academic Knowledge Graphs
Fanjin Zhang, Zhengyang Wang, Ruixuan Huang +7
Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-horizon tasks. Current tool-u…
EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery
Amy Xin, Jiening Siow, Junjie Wang +5
LLM-based agents have shown increasing potential in automating scientific discovery. Given an optimizable metric and an execution environment, they can propose, validate, and itera…
Cross-Source Reasoning-based Correction for Author Name Disambiguation
Fanjin Zhang, Yunhe Pang, Bo Chen +4
Author name disambiguation is a critical challenge in academic search systems, often addressed through from-scratch and real-time disambiguation approaches. However, current algori…
RPC-Bench: A Fine-grained Benchmark for Research Paper Comprehension
Yelin Chen, Fanjin Zhang, Suping Sun +8
Understanding research papers remains challenging for foundation models due to specialized scientific discourse and complex figures and tables, yet existing benchmarks offer limite…
Small Language Model Makes an Effective Long Text Extractor
Yelin Chen, Fanjin Zhang, Jie Tang
Named Entity Recognition (NER) is a fundamental problem in natural language processing (NLP). However, the task of extracting longer entity spans (e.g., awards) from extended texts…
SAM Decoding: Speculative Decoding via Suffix Automaton
Yuxuan Hu, Ke Wang, Xiaokang Zhang +4
Speculative decoding (SD) has been demonstrated as an effective technique for lossless LLM inference acceleration. Retrieval-based SD methods, one kind of model-free method, have y…
GuARD: Effective Anomaly Detection through a Text-Rich and Graph-Informed Language Model
Yunhe Pang, Bo Chen, Fanjin Zhang +3
Anomaly detection on text-rich graphs is widely prevalent in real life, such as detecting incorrectly assigned academic papers to authors and detecting bots in social networks. The…
BOND: Bootstrapping From-Scratch Name Disambiguation with Multi-task Promoting
Yuqing Cheng, Bo Chen, Fanjin Zhang +1
From-scratch name disambiguation is an essential task for establishing a reliable foundation for academic platforms. It involves partitioning documents authored by identically name…
PST-Bench: Tracing and Benchmarking the Source of Publications
Fanjin Zhang, Kun Cao, Yukuo Cen +3
Tracing the source of research papers is a fundamental yet challenging task for researchers. The billion-scale citation relations between papers hinder researchers from understandi…
OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining
Fanjin Zhang, Shijie Shi, Yifan Zhu +19
With the rapid proliferation of scientific literature, versatile academic knowledge services increasingly rely on comprehensive academic graph mining. Despite the availability of p…
Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit
Bo Chen, Jing Zhang, Fanjin Zhang +5
Name disambiguation -- a fundamental problem in online academic systems -- is now facing greater challenges with the increasing growth of research papers. For example, on AMiner, a…
Understanding WeChat User Preferences and "Wow" Diffusion
Fanjin Zhang, Jie Tang, Xueyi Liu +9
WeChat is the largest social instant messaging platform in China, with 1.1 billion monthly active users. "Top Stories" is a novel friend-enhanced recommendation engine in WeChat, i…
Self-supervised Learning: Generative or Contrastive
Xiao Liu, Fanjin Zhang, Zhenyu Hou +4
Deep supervised learning has achieved great success in the last decade. However, its deficiencies of dependence on manual labels and vulnerability to attacks have driven people to…