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20212026
most citedREFinD: Relation Extraction Financial Dataset

27 citations · 51 across the 21 of their papers we have counts for

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Showing 2025 · cs.CLShow all

5 papers · 2 filters

cs.CL2025

A Variational Approach for Mitigating Entity Bias in Relation Extraction

Samuel Mensah, Elena Kochkina, Jabez Magomere +3

Mitigating entity bias is a critical challenge in Relation Extraction (RE), where models often rely excessively on entities, resulting in poor generalization. This paper presents a…

cs.CL2025

Conservative Bias in Large Language Models: Measuring Relation Predictions

Toyin Aguda, Erik Wilson, Allan Anzagira +2

Large language models (LLMs) exhibit pronounced conservative bias in relation extraction tasks, frequently defaulting to No_Relation label when an appropriate option is unavailable…

cs.CL2025

Calibrating LLM Confidence by Probing Perturbed Representation Stability

Reza Khanmohammadi, Erfan Miahi, Mehrsa Mardikoraem +5

Miscalibration in Large Language Models (LLMs) undermines their reliability, highlighting the need for accurate confidence estimation. We introduce CCPS (Calibrating LLM Confidence…

cs.CL2025★ 1 cited

FinNLI: Novel Dataset for Multi-Genre Financial Natural Language Inference Benchmarking

Jabez Magomere, Elena Kochkina, Samuel Mensah +2

We introduce FinNLI, a benchmark dataset for Financial Natural Language Inference (FinNLI) across diverse financial texts like SEC Filings, Annual Reports, and Earnings Call transc…

cs.CL2025

Grounding LLM Reasoning with Knowledge Graphs

Alfonso Amayuelas, Joy Sain, Simerjot Kaur +1

Large Language Models (LLMs) excel at generating natural language answers, yet their outputs often remain unverifiable and difficult to trace. Knowledge Graphs (KGs) offer a comple…