4 papers
DICE: Decoupling Capability from Intervention Necessity in LLM Tutoring
Sayantan Pal, Kaiyi Ji, Rohini K. Srihari
Fluent guidance is not the same as useful intervention. LLM tutors are typically trained to generate the next teacher utterance, implicitly assuming that every student turn warrant…
GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning
Anushka Tiwari, Sayantan Pal, Rohini K. Srihari +1
Prompt-based continual learning (CL) offers a parameter-efficient way to adapt large language models (LLMs) across task sequences. However, existing methods often rely on task-awar…
Beyond Discrete Personas: Personality Modeling Through Journal Intensive Conversations
Sayantan Pal, Souvik Das, Rohini K. Srihari
Large Language Models (LLMs) have significantly improved personalized conversational capabilities. However, existing datasets like Persona Chat, Synthetic Persona Chat, and Blended…
Mitigating Clickbait: An Approach to Spoiler Generation Using Multitask Learning
Sayantan Pal, Souvik Das, Rohini K. Srihari
This study introduces 'clickbait spoiling', a novel technique designed to detect, categorize, and generate spoilers as succinct text responses, countering the curiosity induced by…