Chanakya Ekbote

18 papers A* 3Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interleaved Head Attention. CoRR Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal, Rishabh Tiwari, Devvrit Khatri, David Brandfonbrener, Paul Pu Liang, Inderjit S. Dhillon, Manzil Zaheer
2026	J	`jnl`	OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization. CoRR Keane Ong, Sabri Boughorbel, Luwei Xiao, Chanakya Ekbote, Wei Dai, Ao Qu, Jingyao Wu, Rui Mao, Ehsan Hoque, Erik Cambria, Gianmarco Mengaldo, Paul Pu Liang
2025	J	`jnl`	MURPHY: Multi-Turn GRPO for Self Correcting Code Generation. CoRR Chanakya Ekbote, Vijay Lingam, Behrooz Omidvar-Tehrani, Jun Huan, Sujay Sanghavi, Anoop Deoras, Stefano Soatto
2025	J	`jnl`	PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts. CoRR Hengzhi Li, Brendon Jiang, Alexander Naehu, Regan Song, Justin Zhang, Megan Tjandrasuwita, Chanakya Ekbote, Steven-Shine Chen, Adithya Balachandran, Wei Dai, Rebecca Chang, Paul Pu Liang
2025	J	`jnl`	QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Training. CoRR Wei Dai, Peilin Chen, Chanakya Ekbote, Paul Pu Liang
2025	—	`conf`	TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models. ACL (Findings) Jaewoo Lee, Keyang Xuan, Chanakya Ekbote, Sandeep Polisetty, Yi R. Fung, Paul Pu Liang
2025	J	`jnl`	TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models. CoRR Jaewoo Lee, Keyang Xuan, Chanakya Ekbote, Sandeep Polisetty, Yi R. Fung, Paul Pu Liang
2025	A*	`conf`	Understanding the Emergence of Multimodal Representation Alignment. ICML Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin, Paul Pu Liang
2025	J	`jnl`	Understanding the Emergence of Multimodal Representation Alignment. CoRR Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin, Paul Pu Liang
2025	J	`jnl`	What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains. CoRR Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman, Jason D. Lee, Michael Gastpar, Ashok Vardhan Makkuva, Paul Pu Liang
2024	A*	`conf`	Local to Global: Learning Dynamics and Effect of Initialization for Transformers. NeurIPS Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Hyeji Kim, Michael Gastpar, Chanakya Ekbote
2024	J	`jnl`	Local to Global: Learning Dynamics and Effect of Initialization for Transformers. CoRR Ashok Vardhan Makkuva, Marco Bondaschi, Chanakya Ekbote, Adway Girish, Alliot Nagle, Hyeji Kim, Michael Gastpar
2023	A*	`conf`	FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. NeurIPS Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi
2023	J	`jnl`	FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. CoRR Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam
2022	—	`conf`	A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks. ECML/PKDD (2) Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
2022	J	`jnl`	Biological Sequence Design with GFlowNets. CoRR Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
2022	J	`jnl`	Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. CoRR Chanakya Ekbote, Moksh Jain, Payel Das, Yoshua Bengio
2021	J	`jnl`	A Piece-wise Polynomial Filtering Approach for Graph Neural Networks. CoRR Vijay Lingam, Chanakya Ekbote, Manan Sharma, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam