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title: AI for Mental Health
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<a href="{{ site.base }}/research.html">Research</a> > AI for Mental Health

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                <h3 class="card-title">Counseling Dialogue Understanding</h3>
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                <div class="card-text d-inline-block">Given a sequence of utterances from the counseling dialogue, the task is to understand the dialogue-acts and response-acts. These acts are further exploited to generate effective response generation.</div>

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                <small class="text-muted">Publications: <span style="color: brown;"> <b>WSDM 2022</b></span></small>
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                <h3 class="card-title">Counseling Dialogue Summarization</h3>
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                <div class="card-text d-inline-block">Given a sequence of counseling dialogue, the task is to generate a dialogue summary aka counseling note corresponding to each session.</div>
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                <small class="text-muted">Publications: <span style="color: brown;"> <b>KDD 2022</b></span></small>
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                <h3 class="card-title">Counseling Dialogue Generation</h3>
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                <div class="card-text d-inline-block"> Given a context of counseling dialogue, our focus is on exploiting reinforcement learning and domain knowledge to generate effective responses.</div>

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                <small class="text-muted">Publications: <span style="color: brown;"> <b>WWWW 2023</b></span></small>
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                <h3 class="card-title">Counseling Analysis</h3>
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                <div class="card-text d-inline-block"> We work on analyzing counseling conversations in multiple counseling methods, including individual and peer counseling methods. The agenda is to understand users' behavior viz. intents, criticism, readability during discussions on symptoms, reasoning, gender, patient story, etc., on online mental health communities and virtual mental health assistants for effective counseling.</div>

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                <small class="text-muted">Publications: <span style="color: brown;"> <b>ICWSM 2022</b></span></small>
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