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20242026
most citedLarge Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction

Chengzhi Liu, Yuzhe Yang, Sophia Xiao Pu +14

Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stal…

cs.CL2025

AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation

Elizabeth Fons, Elena Kochkina, Rachneet Kaur +5

This paper explores the potential of large language models (LLMs) to generate financial reports from time series data. We propose a framework encompassing prompt engineering, model…

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★ 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.CL2024★ 4 cited

Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency

Toyin Aguda, Suchetha Siddagangappa, Elena Kochkina +4

Collecting labeled datasets in finance is challenging due to scarcity of domain experts and higher cost of employing them. While Large Language Models (LLMs) have demonstrated rema…