Subham Sekhar Sahoo

17 papers A* 6Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Scaling Beyond Masked Diffusion Language Models. CoRR Subham Sekhar Sahoo, Jean-Marie Lemercier, Zhihan Yang, Justin Deschenaux, Jingyu Liu, John Thickstun, Ante Jukic
2026	J	`jnl`	The Diffusion Duality, Chapter II: Ψ-Samplers and Efficient Curriculum. CoRR Justin Deschenaux, Caglar Gulcehre, Subham Sekhar Sahoo
2025	A*	`conf`	Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models. ICLR Marianne Arriola, Aaron Gokaslan, Justin T. Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov
2025	J	`jnl`	Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models. CoRR Marianne Arriola, Aaron Gokaslan, Justin T. Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov
2025	J	`jnl`	Esoteric Language Models. CoRR Subham Sekhar Sahoo, Zhihan Yang, Yash Akhauri, Johnna Liu, Deepansha Singh, Zhoujun Cheng, Zhengzhong Liu, Eric Xing, John Thickstun, Arash Vahdat
2025	J	`jnl`	Remasking Discrete Diffusion Models with Inference-Time Scaling. CoRR Guanghan Wang, Yair Schiff, Subham Sekhar Sahoo, Volodymyr Kuleshov
2025	A*	`conf`	Simple Guidance Mechanisms for Discrete Diffusion Models. ICLR Yair Schiff, Subham Sekhar Sahoo, Hao Phung, Guanghan Wang, Sam Boshar, Hugo Dalla-torre, Bernardo P. de Almeida, Alexander M. Rush, Thomas Pierrot, Volodymyr Kuleshov
2025	A*	`conf`	The Diffusion Duality. ICML Subham Sekhar Sahoo, Justin Deschenaux, Aaron Gokaslan, Guanghan Wang, Justin T. Chiu, Volodymyr Kuleshov
2025	J	`jnl`	The Diffusion Duality. CoRR Subham Sekhar Sahoo, Justin Deschenaux, Aaron Gokaslan, Guanghan Wang, Justin T. Chiu, Volodymyr Kuleshov
2024	J	`jnl`	Simple Guidance Mechanisms for Discrete Diffusion Models. CoRR Yair Schiff, Subham Sekhar Sahoo, Hao Phung, Guanghan Wang, Sam Boshar, Hugo Dalla-torre, Bernardo P. de Almeida, Alexander Rush, Thomas Pierrot, Volodymyr Kuleshov
2024	J	`jnl`	Simple and Effective Masked Diffusion Language Models. CoRR Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T. Chiu, Alexander M. Rush, Volodymyr Kuleshov
2023	A*	`conf`	Backpropagation through Combinatorial Algorithms: Identity with Projection Works. ICLR Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica, Vít Musil, Volodymyr Kuleshov, Georg Martius
2023	J	`jnl`	Diffusion Models With Learned Adaptive Noise. CoRR Subham Sekhar Sahoo, Aaron Gokaslan, Chris De Sa, Volodymyr Kuleshov
2023	A*	`conf`	Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows. ICML Phillip Si, Zeyi Chen, Subham Sekhar Sahoo, Yair Schiff, Volodymyr Kuleshov
2022	J	`jnl`	Gradient Backpropagation Through Combinatorial Algorithms: Identity with Projection Works. CoRR Subham Sekhar Sahoo, Marin Vlastelica, Anselm Paulus, Vít Musil, Volodymyr Kuleshov, Georg Martius
2021	A*	`conf`	Scaling Symbolic Methods using Gradients for Neural Model Explanation. ICLR Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
2020	J	`jnl`	Scaling Symbolic Methods using Gradients for Neural Model Explanation. CoRR Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick F. Riley