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cs.CL2025

Leveraging the Power of Large Language Models in Entity Linking via Adaptive Routing and Targeted Reasoning

Yajie Li, Albert Galimov, Mitra Datta Ganapaneni +4

Entity Linking (EL) has traditionally relied on large annotated datasets and extensive model fine-tuning. While recent few-shot methods leverage large language models (LLMs) throug…

cs.CL2025

DEEPAMBIGQA: Ambiguous Multi-hop Questions for Benchmarking LLM Answer Completeness

Jiabao Ji, Min Li, Priyanshu Kumar +2

Large language models (LLMs) with integrated search tools show strong promise in open-domain question answering (QA), yet they often struggle to produce complete answer set to comp…

cs.CL2025

Comprehensive Evaluation for a Large Scale Knowledge Graph Question Answering Service

Saloni Potdar, Daniel Lee, Omar Attia +8

Question answering systems for knowledge graph (KGQA), answer factoid questions based on the data in the knowledge graph. KGQA systems are complex because the system has to underst…

cs.CL2025

KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs

Zelin Zhou, Simone Conia, Daniel Lee +6

Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English l…

cs.CL2024

Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs

Simone Conia, Daniel Lee, Min Li +3

Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages. These variations may also be caused by tr…

cs.CL2024

Do Large Language Models Have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMs

Yanzhu Guo, Simone Conia, Zelin Zhou +3

Current Large Language Models (LLMs) are predominantly designed with English as the primary language, and even the few that are multilingual tend to exhibit strong English-centric…