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About me:
I am a fourth-year PhD student at University of Washington Seattle where I am working with Prof. Jeffery A. Bilmes. I like to work on improving the efficiency of large-scale models, for both training and inference; with the help of submodular optimization. Checkout labeltrain.ai for our ongoing data/label efficient machine learning collaboratoin. In summer'24 I am interning at NVIDIA - Applied Deep Learning Research Team.
Before joining PhD program, I completed my undergraduate degree at IIT Delhi, where I worked with Dr Sumeet Agarwal. I'm also an avid photographer (Checkout my Unsplash) and hiker! When not working, I can be found messing around with my camera, google earth, or hiking some beautiful mountains in North Cascades. (Most Recent Hike: Trapper Peak).
Recent Updates
[Sept 2024] Deep Submodular Peripteral Networks to appear at NeurIPS'24 as spotlight!
[June 2024] 2 Papers (COBRA and DOVE) will appear in DMLR workshop for ICML'24 as poster and oral talk, respectively.
[June 2024] DOVE will appear in Models of Human Feedback for AI Alignment workshop for ICML'24 as a poster.
[May 2024] New preprint COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Learning.
[May 2024] "An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models" got accepted at ACL Findings.
[Mar 2024] New preprint out - Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization
[Mar 2024] New preprint out - Deep Submodular Peripteral Network
[Mar 2024] I will join NVIDIA as research intern in Summers!
Preprint(s)
COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Learning
Arnav Das*, Gantavya Bhatt*, Lilly Kumari, Sahil Verma, Jeff Bilmes
[Poster] In DMLR workshop at ICML'24
Under Review
Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization
Hritik Bansal*, Ashima Suvarna*, Gantavya Bhatt*, Nanyun Peng, Kai-Wei Chang, Aditya Grover
[Oral] In DMLR workshop at ICML'24
[Poster] In MHFAI Alignment workshop at ICML'24
Conference and Workshop Publications
Deep Submodular Peripteral Networks
Gantavya Bhatt*, Arnav Das*, Jeff Bilmes
[Spotlight] In Neural Information Processing Systems (NeurIPS'24)
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
Gantavya Bhatt*, Yifang Chen*, Arnav Das*, Jifan Zhang*, Sang Truong, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Jordan P Ash, Robert D Nowak
[Poster] Accepted at ACL'24 (Findings)
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning
Jifan Zhang*, Yifang Chen*, Gregory Canal, Arnav Das†, Gantavya Bhatt†, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak
In Adaptive Experimental Design and Active Learning in the Real World workshop at NeurIPS'23.
Accepted at DMLR'24
RadarHD: Demonstrating Lidar-like Point Clouds from mmWave Radar
Akarsh Prabhakara, Tao Jin, Arnav Das*, Gantavya Bhatt*, Lilly Kumari, Elahe Soltanaghei, Jeff Bilmes, Swarun Kumar, Anthony Rowe
In Annual International Conference On Mobile Computing And Networking ACM MobiCom '23
High Resolution Point Clouds from mmWave Radar
Akarsh Prabhakara, Tao Jin, Arnav Das*, Gantavya Bhatt*, Lilly Kumari, Elahe Soltanaghei, Jeff Bilmes, Swarun Kumar, Anthony Rowe
In IEEE International Conference on Robotics and Automation (ICRA'23)
Matryoshka Representation Learning
Aditya Kusupati*, Gantavya Bhatt*, Aniket Rege*, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, and Ali Farhadi
[Poster] In Neural Information Processing Systems (NeurIPS'22)
Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models
Hritik Bansal*, Gantavya Bhatt*, Pankaj Malhotra and Prathosh AP
In International joint Conference on Neural Networks (IJCNN'21)
Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?
Hritik Bansal*, Gantavya Bhatt* and Sumeet Agarwal
In Proceedings of the Society for Computation in Linguistics: Vol. 4 , Article 38.
Decay RNN
How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?
Gantavya Bhatt*, Hritik Bansal*, Rishubh Singh* and Sumeet Agarwal
In Proceedings of the Society for Computation in Linguistics: Vol. 4 , Article 38.