Search Results for author: Amith Ananthram

Found 6 papers, 1 papers with code

Multi-Modal Emotion Detection with Transfer Learning

no code implementations13 Nov 2020 Amith Ananthram, Kailash Karthik Saravanakumar, Jessica Huynh, Homayoon Beigi

To address these two challenges, we present a multi-modal approach that first transfers learning from related tasks in speech and text to produce robust neural embeddings and then uses these embeddings to train a pLDA classifier that is able to adapt to previously unseen emotions and domains.

Speaker Identification Transfer Learning

Event-Guided Denoising for Multilingual Relation Learning

no code implementations COLING 2020 Amith Ananthram, Emily Allaway, Kathleen McKeown

General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that produces state-of-the-art results across many benchmarks.

Denoising Relation +1

Event Guided Denoising for Multilingual Relation Learning

no code implementations4 Dec 2020 Amith Ananthram, Emily Allaway, Kathleen McKeown

General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that produces state-of-the-art results across many benchmarks.

Denoising Relation +1

Seeded Hierarchical Clustering for Expert-Crafted Taxonomies

no code implementations23 May 2022 Anish Saha, Amith Ananthram, Emily Allaway, Heng Ji, Kathleen McKeown

Practitioners from many disciplines (e. g., political science) use expert-crafted taxonomies to make sense of large, unlabeled corpora.

Clustering

Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence

1 code implementation29 May 2023 Gengyu Wang, Kate Harwood, Lawrence Chillrud, Amith Ananthram, Melanie Subbiah, Kathleen McKeown

We present a new fact-checking benchmark, Check-COVID, that requires systems to verify claims about COVID-19 from news using evidence from scientific articles.

Fact Checking Sentence

Social Orientation: A New Feature for Dialogue Analysis

no code implementations26 Feb 2024 Todd Morrill, Zhaoyuan Deng, Yanda Chen, Amith Ananthram, Colin Wayne Leach, Kathleen McKeown

Based on these results showing the utility of social orientation tags for dialogue outcome prediction tasks, we release our data sets, code, and models that are fine-tuned to predict social orientation tags on dialogue utterances.

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