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Souvik Das

10 papers hereh-index 6165 citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author4

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.IR1
  • cs.NE1
same name
  • Souvik Das — 12 papers, h 79
  • Souvik Das — 7 papers, h 3
  • Souvik Das — 5 papers, h 2
  • Souvik Das — 5 papers
  • Souvik Das — 5 papers, h 5
  • Souvik Das — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedProto: A Neural Cocktail for Generating Appealing Conversations

5 citations · 13 across the 10 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024★ 2 cited

Entropy Guided Extrapolative Decoding to Improve Factuality in Large Language Models

Souvik Das, Lifeng Jin, Linfeng Song +3

Large language models (LLMs) exhibit impressive natural language capabilities but suffer from hallucination -- generating content ungrounded in the realities of training data. Rece…

cs.CL2024

Improving Dialog Safety using Socially Aware Contrastive Learning

Souvik Das, Rohini K. Srihari

State-of-the-art conversational AI systems raise concerns due to their potential risks of generating unsafe, toxic, unethical, or dangerous content. Previous works have developed d…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.