Papers by Kumar Pratik

2 papers
A Hybrid Supervised-LLM Pipeline for Actionable Suggestion Mining in Unstructured Customer Reviews (2026.eacl-industry)

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Challenge: Existing approaches to extract actionable suggestions from customer reviews are often mixed-intent, unstructured text.
Approach: They propose a hybrid pipeline that uses a RoBERTa classifier and a precision–recall surrogate to extract actionable suggestions from customer reviews.
Outcome: The proposed pipeline outperforms prompt-only, rule-based, and classifier-only baselines in extraction accuracy and cluster coherence.
Local Look-Ahead Guidance via Verifier-in-the-Loop for Automated Theorem Proving (2025.findings-acl)

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Challenge: Recent methods for AI reasoning require applying variants of reinforcement learning (RL) on rolled out trajectories, even for step-wise rewards, or large quantities of human-annotated trajectory data.
Approach: They propose a verifier-in-the-loop design that uses an automated verifier to give intermediate feedback at each step of the reasoning process.
Outcome: The proposed model improves on the Automatic Theorem Proving task using Lean as the verifier.

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