Papers by Pulkit Bansal

2 papers
From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations (2026.findings-acl)

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Challenge: DeFactoX integrates Direct Preference Optimization (DPO) with Curriculum learning to align machine-generated explanations with human reasoning.
Approach: They propose a framework that integrates Direct Preference Optimization (DPO) with Curriculum learning to align machine-generated explanations with human reasoning.
Outcome: The proposed framework combines Direct Preference Optimization (DPO) with Curriculum learning to align machine-generated explanations with human reasoning.
Finding Needles in Images: Can Multi-modal LLMs Locate Fine Details? (2025.acl-long)

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Challenge: Recent advances in Multi-modal Large Language Models (MLLMs) have fundamentally transformed how machines understand and reason about visual information.
Approach: They propose a benchmark to evaluate MLLMs' ability to locate and reason about fine-grained details within complex documents including newspapers, menus, and lecture images.
Outcome: The proposed method improves on existing methods and shows that it can handle fine-grained document understanding tasks.

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