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20242026
most citedOpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG

1 citations · 4 across the 15 of their papers we have counts for

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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.CL20261 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.CL2026

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.CL2026

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.CL20261 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.CL2026

Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation

Rui Qi, Fengran Mo, Yufeng Chen +7

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