activity
20242026
most citedMaximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities

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

collaborators

5 papers

cs.LG2026

GeoLAN: Geometric Learning of Latent Explanatory Directions in Large Language Models

Tianyu Bell Pan, Damon L. Woodard

Large language models (LLMs) demonstrate strong performance, but they often lack transparency. We introduce GeoLAN, a training framework that treats token representations as geomet…

cs.CL2026

Plato's Cave: A Human-Centered Research Verification System

Matheus Kunzler Maldaner, Raul Valle, Junsung Kim +9

The growing publication rate of research papers has created an urgent need for better ways to fact-check information, assess writing quality, and identify unverifiable claims. We p…

cs.LG2025

Lyapunov-Stable Adaptive Control for Multimodal Concept Drift

Tianyu Bell Pan, Mengdi Zhu, Alexa Jordyn Cole +2

Multimodal learning systems often struggle in non-stationary environments due to concept drift, where changing data distributions can degrade performance. Modality-specific drifts…

cs.CL2024★ 4 cited

Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities

Anushka Swarup, Avanti Bhandarkar, Olivia P. Dizon-Paradis +2

Relation extraction is a Natural Language Processing task that aims to extract relationships from textual data. It is a critical step for information extraction. Due to its wide-sc…

cs.CR2024★ 1 cited

Is the Digital Forensics and Incident Response Pipeline Ready for Text-Based Threats in LLM Era?

Avanti Bhandarkar, Ronald Wilson, Anushka Swarup +2

In the era of generative AI, the widespread adoption of Neural Text Generators (NTGs) presents new cybersecurity challenges, particularly within the realms of Digital Forensics and…