Grad Student Researcher @MIT, prev: Applied Scientist @Microsoft, MS @UCberkeley. Interested in AI, ML and NLP

Joined June 2020
Shrestha Mohanty retweeted
✨ Huge thanks to my excellent collaborators for never giving up — perseverance pays off! What a fantastic way to wrap up @IgluContest: Interactive Grounded Language Understanding in a Collaborative Environment. Grateful for this journey! 🚀💬 Online evaluation remains a significant open challenge for agentic systems! #NeurIPS #AI #HumanAIInteraction iglu-contest.net/
What a way to wrap up @IgluContest! Our paper “IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents” accepted to @SIGIRConf including: 1) rich multi-modal dataset 2) A data collection tool 3) An online eval framework #SIGIR2025
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So happy to share that our work has been accepted to @SIGIRConf. Thank you to my amazing collaborators! @NegarEmpr, Andrea Tupini, Yuxuan Sun, @Tviskaron, @artemZholus, @Cote_Marc and @julia_kiseleva Pre-print: arxiv.org/pdf/2407.08898
What a way to wrap up @IgluContest! Our paper “IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents” accepted to @SIGIRConf including: 1) rich multi-modal dataset 2) A data collection tool 3) An online eval framework #SIGIR2025
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Excited to share our work at @coling2025! While I couldn’t attend in person, @jad_kabbara will be presenting today at the 1:30 PM poster session. Come by to learn how we’re using LLMs to improve understanding in social conversations! #COLING2025 #NLProc
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We also introduce the Human-annotated Salient Excerpts (HSE) dataset, a collection of conversation highlights on topics like public health and safety, annotated with social attributes to enable better contextual understanding.
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✅ Results: Contextualized excerpts improve readability and understanding, though LLMs still face challenges in grasping nuanced social details. 🚀 By bridging gaps in understanding, we aim to develop empathy and create tools for more inclusive conversations.
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Shrestha Mohanty retweeted
Touching down in Vancouver 🛬 for #NeurIPS2024! I'll be presenting our "Consent in Crisis" work on the 11th: arxiv.org/abs/2407.14933 Reach out to catch up or chat about: - Training data / methods - AI uses & impacts - Multilingual scaling
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Just arrived at EMNLP in sunny Miami! 🌞 Excited to reconnect and meet new friends. Happy to chat about our works on 1)Bridging context gaps for better understanding in social conversations 2)Exploring truth and political bias in language models. #EMNLP #NLP #SocialConversations
📣📣Do language models only trained to predict truth from falsehood still display a political bias? 🤔Surprisingly, it seems so!  Our paper "On the Relationship between Truth and Political Bias in Language Models”, has been accepted to EMNLP 2024
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Shrestha Mohanty retweeted
[Please RT] I’m recruiting PhD students to work with me at @UW! I’m looking for students passionate about developing new *social media algorithms*, both broadly and within the scope of this NSF grant: tinyurl.com/395yfphd More info: faculty.washington.edu/msave… @UW / @UW_iSchool
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Woohoo!! Congrats!! 🎉 Here's to many more milestones! ✨ #ProudMoment #WellDeserved
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Super excited to share that our paper, "On the Relationship between Truth and Political Bias in Language Models", has been accepted to EMNLP 2024 Main! 🎉 We explore how models trained on truthful data might exhibit a political bias. #EMNLP2024
📣📣Do language models only trained to predict truth from falsehood still display a political bias? 🤔Surprisingly, it seems so!  Our paper "On the Relationship between Truth and Political Bias in Language Models”, has been accepted to EMNLP 2024
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Shrestha Mohanty retweeted
📢 Who contributes most to politically polarized speech on Reddit and Twitter? As we come into the final stretch of the presidential election season, we present our work out of @CCCatMIT a large-scale analysis (2.5 billion tweets/comments) of politically polarized speech.
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Shrestha Mohanty retweeted
Our paper addresses the challenges of developing interactive AI agents capable of understanding and executing grounded natural language instructions through @IgluContest, which timely demonstrates the importance of testing AI agents in dynamic environments with real users! When we proposed this idea 3.5 years ago, it felt so far ahead! Now, progress is evident, but we still need to take the final steps toward proper realistic evaluation that leads to groundbreaking discoveries. A big thank you to all the collaborators who have been part of this amazing journey over the past years, pushing the frontiers of AI research in various institutions and directions now! One important lesson I’ve learned is that experiments might fail, ideas might not work, and papers might be rejected—but focus on the growth of the people you are working with. At the end of the day, it’s all about the people! @NegarEmpr @shremoha @artemZholus Andrea Tupini Yuxuan Sun @Cote_Marc and many others arxiv.org/abs/2407.08898
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Last month, I had a lot of fun giving a lightning talk about some new ideas I'm stewing on regarding generative AI and human agency. It touches on only the first piece of a longer argument we unpack in a recent white paper. youtube.com/watch?v=Do3opAtF… Summary 🧵👇
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Shrestha Mohanty retweeted
🚨 We all complain a lot about reviewers/ACs/SACs in the ML/NLP community.   But why not look at the data to see what’s going on? I found some crazy statistics about who is doing/not doing this service in the *CL community. 😱 orionweller.github.io/blog/2… 🧵
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