Ashok Urlana
Scholar

Ashok Urlana

Google Scholar ID: v5wiUEsAAAAJ
PhD Fellow at IIIT-Hyderabad and Researcher at TCS Research
LLMs attributionExplainabilityNLPMachine learningRobotics
Citations & Impact
All-time
Citations
154
 
H-index
8
 
i10-index
7
 
Publications
20
 
Co-authors
13
list available
Resume (English only)
Academic Achievements
  • - Publications:
  • - Behind the Words: A Comprehensive Study of Bias Detection Methods in LLMs
  • - HalluCounter: Reference-free LLM Hallucination Detection in the Wild!
  • - No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models
  • - Agent Ideate: A Framework for Product Idea Generation from Patents Using Agentic AI
  • - No Size Fits All: The Perils and Pitfalls of Leveraging LLMs Vary with Company Size
  • - LimGen: Probing the LLMs for Generating Suggestive Limitations of Research Papers
  • - Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Survey
  • - Assessing Translation Capabilities of Large Language Models involving English and Indian Languages
  • - Exploring News Summarization and Enrichment in a Highly Resource-Scarce Indian Language: A Case Study of Mizo
  • - Preprints:
  • - AGIC: Attention-Guided Image Captioning to Improve Caption Relevance
  • - LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey
  • - Master's Thesis: Enhancing Text Summarization for Indian Languages: Mono, Multi and Cross-lingual Approaches
Research Experience
  • - IIIT-Hyderabad, PhD Fellow, January 2025 - present
  • - TCS Research, Researcher, August 2023 - present
  • - IIIT-Hyderabad, Masters by Research, July 2020 - July 2023
  • - IIIT-Hyderabad, Research Intern, May 2019 - June 2020
Education
  • - PhD candidate, IIIT-Hyderabad, advisors: Ponnurangam Kumaraguru (PK) and Rahul Mishra
  • - Master's, International Institute of Information Technology-Hyderabad, advisor: Manish Shrivastava
  • - Bachelor's Degree, RGUKT-Nuzvid
Background
  • Research interests include unlearning, explainability and interpretability of LLMs, multimodal, multilingual text summarization for low-resource languages, and bio-inspired algorithms.
Miscellany
  • Personal interests not provided.