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20232026
most citedUnifying Graph Convolution and Contrastive Learning in Collaborative Filtering

26 citations · 77 across the 36 of their papers we have counts for

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15 papers · 1 filter

cs.CL2026

Search-on-Graph-R1: Training Large Language Models to Search Knowledge Graphs with Reinforcement Learning

Jia Ao Sun, Hao Yu, Fengran Mo +4

Knowledge graph question answering (KGQA) requires navigating from topic entities to an answer several relations away. Recent methods prompt a frontier LLM to explore the graph thr…

cs.CL2026

CroSearch-R1: Better Leveraging Cross-lingual Knowledge for Retrieval-Augmented Generation

Rui Qi, Fengran Mo, Sijin Lu +3

A multilingual collection may contain useful knowledge in other languages to supplement and correct the facts in the original language for Retrieval-Augmented Generation (RAG). How…

cs.CL2026

ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting

Yuxing Tian, Fengran Mo, Weixu Zhang +2

The strong capabilities of recent Large Language Models (LLMs) have made them highly effective for zero-shot re-ranking task. Attention-based re-ranking methods, which derive relev…

cs.CL2026★ 1 cited

OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG

Fengran Mo, Zhan Su, Yuchen Hui +6

The development of large language models (LLMs) has achieved superior performance in a range of downstream tasks, including LLM-based retrieval-augmented generation (RAG). The qual…

cs.CL2026

Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation

Rui Qi, Fengran Mo, Yufeng Chen +6

Multilingual retrieval-augmented generation (MRAG) requires models to effectively acquire and integrate beneficial external knowledge from multilingual collections. However, most e…

cs.CL2025

Measuring the Impact of Lexical Training Data Coverage on Hallucination Detection in Large Language Models

Shuo Zhang, Fabrizio Gotti, Fengran Mo +1

Hallucination in large language models (LLMs) is a fundamental challenge, particularly in open-domain question answering. Prior work attempts to detect hallucination with model-int…

cs.CL2025

FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs

Yan Wang, Keyi Wang, Shanshan Yang +12

Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale disclosures. As financial reports…

cs.CL2025★ 1 cited

Search-on-Graph: Iterative Informed Navigation for Large Language Model Reasoning on Knowledge Graphs

Jia Ao Sun, Hao Yu, Fabrizio Gotti +6

Large language models (LLMs) augmented with knowledge graphs (KGs) offer a promising approach for knowledge-intensive reasoning. Central to this approach is the selection of approp…

cs.CL2025

An Entity Linking Agent for Question Answering

Yajie Luo, Yihong Wu, Muzhi Li +5

Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking natural language mentions to KB…

cs.CL2025★ 1 cited

FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information

Yan Wang, Lingfei Qian, Xueqing Peng +18

Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Reporting Language) provides a standard fo…

cs.CL2024★ 3 cited

A Survey of Conversational Search

Fengran Mo, Kelong Mao, Ziliang Zhao +7

As a cornerstone of modern information access, search engines have become indispensable in everyday life. With the rapid advancements in AI and natural language processing (NLP) te…

cs.CL2024

Boosting Biomedical Concept Extraction by Rule-Based Data Augmentation

Qiwei Shao, Fengran Mo, Jian-Yun Nie

Document-level biomedical concept extraction is the task of identifying biomedical concepts mentioned in a given document. Recent advancements have adapted pre-trained language mod…

cs.CL2024★ 6 cited

A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers

Kaiyu Huang, Fengran Mo, Xinyu Zhang +10

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia…

cs.CL2024★ 1 cited

PAQA: Toward ProActive Open-Retrieval Question Answering

Pierre Erbacher, Jian-Yun Nie, Philippe Preux +1

Conversational systems have made significant progress in generating natural language responses. However, their potential as conversational search systems is currently limited due t…

cs.CL2023★ 1 cited

MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model

Le Zhang, Yihong Wu, Fengran Mo +2

Multi-modal open-domain question answering typically requires evidence retrieval from databases across diverse modalities, such as images, tables, passages, etc. Even Large Languag…