2 citations · 2 across the 3 of their papers we have counts for
8 papers · 1 filter
APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI
Pratyay Banerjee, Masud Moshtaghi, Shivashankar Subramanian +2
Large language models still struggle with reliable long-term conversational memory: simply enlarging context windows or applying naive retrieval often introduces noise and destabil…
Fairness-aware Class Imbalanced Learning
Shivashankar Subramanian, Afshin Rahimi, Timothy Baldwin +2
Class imbalance is a common challenge in many NLP tasks, and has clear connections to bias, in that bias in training data often leads to higher accuracy for majority groups at the…
Evaluating Debiasing Techniques for Intersectional Biases
Shivashankar Subramanian, Xudong Han, Timothy Baldwin +2
Bias is pervasive in NLP models, motivating the development of automatic debiasing techniques. Evaluation of NLP debiasing methods has largely been limited to binary attributes in…
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran +7
More than 200 generic drugs approved by the U.S. Food and Drug Administration for non-cancer indications have shown promise for treating cancer. Due to their long history of safe p…
Deep Ordinal Regression for Pledge Specificity Prediction
Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin
Many pledges are made in the course of an election campaign, forming important corpora for political analysis of campaign strategy and governmental accountability. At present, ther…
Target Based Speech Act Classification in Political Campaign Text
Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin
We study pragmatics in political campaign text, through analysis of speech acts and the target of each utterance. We propose a new annotation schema incorporating domain-specific s…