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20202026
most citedProKnow: Process Knowledge for Safety Constrained and Explainable Question Generation for Mental Health Diagnostic Assistance

19 citations · 41 across the 14 of their papers we have counts for

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12 papers · 1 filter

cs.CL2026

Bag of Tricks or Bag of Myths? Reducing Modeling Complexity with Task Knowledge in Explainable Suicide Risk Assessment

Shlok Shelat, Shrey Salvi, Souvik Roy +2

Assessing suicide risk from social media text is a small-data, high-stakes setting requiring not only severity prediction but also supporting evidence and clinically relevant risk…

cs.CL2026

SelfGraphRAG: Bridging the Supervision Gap in Graph-Based RAG with Synthetic QA Generation

Ben Lagnese, Manas Gaur

Retrieval-augmented generation (RAG) improves large language models by incorporating external knowledge without retraining, but existing methods often underuse the relational struc…

cs.CL2026

Where do LLMs Fall Short in CBT-Guided Affective Reasoning?

Vaishnavi Sinha, Pooja Guttal, Pranay Deep Reddy Katike +5

Cognitive Behavioral Therapy (CBT) provides a structured framework for understanding a user's mental state by examining the interaction between cognitive and behavioral factors. Ho…

cs.CL2024

Abstention vs. Hallucination: Benchmarking LLM Source Attribution for Scientific Citations

Deepa Tilwani, Yash Saxena, Seyedali Mohammadi +5

Large language models (LLMs) increasingly generate citation-backed responses, yet citation hallucination remains a major challenge for trustworthy scientific information access. We…

cs.CL2023

L3 Ensembles: Lifelong Learning Approach for Ensemble of Foundational Language Models

Aidin Shiri, Kaushik Roy, Amit Sheth +1

Fine-tuning pre-trained foundational language models (FLM) for specific tasks is often impractical, especially for resource-constrained devices. This necessitates the development o…

cs.CL20231 cited

Leveraging Knowledge and Reinforcement Learning for Enhanced Reliability of Language Models

Nancy Tyagi, Surjodeep Sarkar, Manas Gaur

The Natural Language Processing(NLP) community has been using crowd sourcing techniques to create benchmark datasets such as General Language Understanding and Evaluation(GLUE) for…