Papers by Gautam Naik

2 papers
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations (P19-1)

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Challenge: Emotion recognition in conversations has gained popularity due to its potential applications. Until now, a large multimodal multi-party emotional conversational database containing more than two speakers per dialogue was missing.
Approach: They propose to extend and enhance EmotionLines by combining 13,000 utterances from Friends dialogues with emotion and sentiment labels.
Outcome: The proposed dataset contains about 13,000 utterances from 1,433 dialogues from the TV-series Friends.
A Continued Pretrained LLM Approach for Automatic Medical Note Generation (2024.naacl-short)

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Challenge: HEAL is the first continuously trained LLaMA2-based LLM for medical conversations . despite the success of LLMs in general capabilities, they often fall short in niche domains like healthcare .
Approach: They propose a 13B LLaMA2-based LLM that is purpose-built for medical conversations and measured on automated scribing.
Outcome: The HEAL LLM outperforms GPT-4 and PMC-LLaMA in PubMedQA with 78.4% accuracy and parity with GPT-LLAMA in generating medical notes.

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