Papers by Aseem Srivastava

3 papers
Knowledge Planning in Large Language Models for Domain-Aligned Counseling Summarization (2024.emnlp-main)

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Challenge: Large Language Models (LLMs) exhibit remarkable capabilities in various generative tasks, but their adaptation to domain-specific intricacies remains challenging.
Approach: They propose to use a planning engine to orchestrate structuring knowledge alignment to achieve high-order planning by encapsulating domain knowledge and leveraging sheaf convolution learning to enhance its understanding of the dialogue’s structural nuances.
Outcome: The proposed framework improves on existing LLMs and shows that it can generate better summaries with better quality and better execution.
Assess and Prompt: A Generative RL Framework for Improving Engagement in Online Mental Health Communities (2025.findings-emnlp)

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Challenge: Empirical results across four notable language models demonstrate significant improvements in attribute elicitation and user engagement.
Approach: They propose a framework that identifies and prompts users to enrich their posts by eliciting missing support attributes.
Outcome: The proposed framework improves engagement and elicits missing information from posts.
Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversation (2026.acl-long)

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Challenge: Recent systems exhibit conversational competence but lack structured mechanisms to evaluate adherence to core therapeutic principles.
Approach: They propose a framework to evaluate therapist-like responses for clinically grounded appropriateness and effectiveness using an ordinal scale.
Outcome: The proposed framework achieves an F-1 score of 63.34 versus the baseline Qwen3 score of 38.56 .

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