Karthik Abinav Sankararaman

73 papers A* 15A 10C 1Journal 42Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Dual-Weighted Reinforcement Learning for Generative Preference Modeling. CoRR Shengyu Feng, Yun He, Shuang Ma, Beibin Li, Yuanhao Xiong, Songlin Li, Karishma Mandyam, Julian Katz-Samuels, Shengjie Bi, Licheng Yu, Hejia Zhang, Karthik Abinav Sankararaman, Han Fang, Riham Mansour, Yiming Yang, Manaal Faruqui
2025	J	`jnl`	Generalized Parallel Scaling with Interdependent Generations. CoRR Harry Dong, David Brandfonbrener, Eryk Helenowski, Yun He, Mrinal Kumar, Han Fang, Yuejie Chi, Karthik Abinav Sankararaman
2025	—	`conf`	Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation. ACL (2) Chengwei Qin, Wenxuan Zhou, Karthik Abinav Sankararaman, Nanshu Wang, Tengyu Xu, Alexander Radovic, Eryk Helenowski, Arya Talebzadeh, Aditya Tayade, Sinong Wang, Shafiq Joty, Han Fang, Hao Ma
2025	J	`jnl`	Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation. CoRR Chengwei Qin, Wenxuan Zhou, Karthik Abinav Sankararaman, Nanshu Wang, Tengyu Xu, Alexander Radovic, Eryk Helenowski, Arya Talebzadeh, Aditya Tayade, Sinong Wang, Shafiq Joty, Han Fang, Hao Ma
2025	J	`jnl`	Reinforcement Learning from User Feedback. CoRR Eric Han, Jun Chen, Karthik Abinav Sankararaman, Xiaoliang Peng, Tengyu Xu, Eryk Helenowski, Kaiyan Peng, Mrinal Kumar, Sinong Wang, Han Fang, Arya Talebzadeh
2025	A*	`conf`	Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization. ICML Zishun Yu, Tengyu Xu, Di Jin, Karthik Abinav Sankararaman, Yun He, Wenxuan Zhou, Zhouhao Zeng, Eryk Helenowski, Chen Zhu, Sinong Wang, Hao Ma, Han Fang
2025	J	`jnl`	Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization. CoRR Zishun Yu, Tengyu Xu, Di Jin, Karthik Abinav Sankararaman, Yun He, Wenxuan Zhou, Zhouhao Zeng, Eryk Helenowski, Chen Zhu, Sinong Wang, Hao Ma, Han Fang
2024	J	`jnl`	Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression. J. Mach. Learn. Res. Aleksandrs Slivkins, Xingyu Zhou, Karthik Abinav Sankararaman, Dylan J. Foster
2024	—	`conf`	Effective Long-Context Scaling of Foundation Models. NAACL-HLT Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma
2024	J	`jnl`	Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals. ACM Trans. Economics and Comput. John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu, Yifan Xu
2024	J	`jnl`	Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following. CoRR Yun He, Di Jin, Chaoqi Wang, Chloe Bi, Karishma Mandyam, Hejia Zhang, Chen Zhu, Ning Li, Tengyu Xu, Hongjiang Lv, Shruti Bhosale, Chenguang Zhu, Karthik Abinav Sankararaman, Eryk Helenowski, Melanie Kambadur, Aditya Tayade, Hao Ma, Han Fang, Sinong Wang
2024	J	`jnl`	On the Equivalence of Graph Convolution and Mixup. Trans. Mach. Learn. Res. Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu
2024	J	`jnl`	Preference Optimization with Multi-Sample Comparisons. CoRR Chaoqi Wang, Zhuokai Zhao, Chen Zhu, Karthik Abinav Sankararaman, Michal Valko, Xuefei Cao, Zhaorun Chen, Madian Khabsa, Yuxin Chen, Hao Ma, Sinong Wang
2024	A*	`conf`	Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation. ICML Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2024	J	`jnl`	The Perfect Blend: Redefining RLHF with Mixture of Judges. CoRR Tengyu Xu, Eryk Helenowski, Karthik Abinav Sankararaman, Di Jin, Kaiyan Peng, Eric Han, Shaoliang Nie, Chen Zhu, Hejia Zhang, Wenxuan Zhou, Zhouhao Zeng, Yun He, Karishma Mandyam, Arya Talabzadeh, Madian Khabsa, Gabriel Cohen, Yuandong Tian, Hao Ma, Sinong Wang, Han Fang
2023	A	`conf`	Allocation Problem in Remote Teleoperation: Online Matching with Offline Reusable Resources and Delayed Assignments. AAMAS Osnat Ackerman Viden, Yohai Trabelsi, Pan Xu, Karthik Abinav Sankararaman, Oleg Maksimov, Sarit Kraus
2023	A*	`conf`	Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression. COLT Aleksandrs Slivkins, Karthik Abinav Sankararaman, Dylan J. Foster
2023	J	`jnl`	Effective Long-Context Scaling of Foundation Models. CoRR Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma
2023	J	`jnl`	Matching algorithms for blood donation. Nat. Mac. Intell. Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
2023	J	`jnl`	On the Equivalence of Graph Convolution and Mixup. CoRR Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu
2023	A*	`conf`	Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? NeurIPS Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu
2023	J	`jnl`	Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? CoRR Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu
2022	J	`jnl`	Adversarial Bandits with Knapsacks. J. ACM Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2022	J	`jnl`	BayesFormer: Transformer with Uncertainty Estimation. CoRR Karthik Abinav Sankararaman, Sinong Wang, Han Fang
2022	J	`jnl`	Improved Adaptive Algorithm for Scalable Active Learning with Weak Labeler. CoRR Yifang Chen, Karthik Abinav Sankararaman, Alessandro Lazaric, Matteo Pirotta, Dmytro Karamshuk, Qifan Wang, Karishma Mandyam, Sinong Wang, Han Fang
2022	J	`jnl`	Online minimum matching with uniform metric and random arrivals. Oper. Res. Lett. Sharmila V. S. Duppala, Karthik Abinav Sankararaman, Pan Xu
2022	A	`conf`	Robust identifiability in linear structural equation models of causal inference. UAI Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
2021	J	`jnl`	Allocation Problems in Ride-sharing Platforms: Online Matching with Offline Reusable Resources. ACM Trans. Economics and Comput. John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2021	A*	`conf`	Bandits with Knapsacks beyond the Worst Case. NeurIPS Karthik Abinav Sankararaman, Aleksandrs Slivkins
2021	A*	`conf`	Beyond log ICML Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
2021	J	`jnl`	Beyond log CoRR Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
2021	A	`conf`	Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship. AISTATS Abishek Sankararaman, Soumya Basu, Karthik Abinav Sankararaman
2021	J	`jnl`	Matching Algorithms for Blood Donation. CoRR Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
2021	A	`conf`	Multi-Armed Bandits with Cost Subsidy. AISTATS Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula
2021	J	`jnl`	Online minimum matching with uniform metric and random arrivals. CoRR Sharmila Duppala, Karthik Abinav Sankararaman, Pan Xu
2021	J	`jnl`	Stochastic Bandits for Multi-platform Budget Optimization in Online Advertising. CoRR Vashist Avadhanula, Riccardo Colini-Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers
2021	A*	`conf`	Stochastic bandits for multi-platform budget optimization in online advertising. WWW Vashist Avadhanula, Riccardo Colini-Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers
2020	J	`jnl`	Advances in Bandits with Knapsacks. CoRR Karthik Abinav Sankararaman, Aleksandrs Slivkins
2020	J	`jnl`	Algorithms to Approximate Column-sparse Packing Problems. ACM Trans. Algorithms Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020	J	`jnl`	Attenuate Locally, Win Globally: Attenuation-Based Frameworks for Online Stochastic Matching with Timeouts. Algorithmica Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020	A*	`conf`	Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AAAI Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
2020	C	`conf`	Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AIES Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
2020	J	`jnl`	Dominate or Delete: Decentralized Competing Bandits with Uniform Valuation. CoRR Abishek Sankararaman, Soumya Basu, Karthik Abinav Sankararaman
2020	J	`jnl`	Improved Approximation Algorithms for Stochastic-Matching Problems. CoRR Marek Adamczyk, Brian Brubach, Fabrizio Grandoni, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020	A*	`conf`	Matching Algorithms for Blood Donation. EC Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
2020	J	`jnl`	Online Stochastic Matching: New Algorithms and Bounds. Algorithmica Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020	J	`jnl`	Robust Identifiability in Linear Structural Equation Models of Causal Inference. CoRR Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
2020	A*	`conf`	The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. ICML Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein
2019	A*	`conf`	A Unified Approach to Online Matching with Conflict-Aware Constraints. AAAI Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas
2019	A*	`conf`	Adversarial Bandits with Knapsacks. FOCS Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2019	A*	`conf`	Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. AAAI John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2019	J	`jnl`	Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours. CoRR Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
2019	J	`jnl`	Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare. CoRR Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu
2019	—	`conf`	Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare. WINE Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu
2019	A	`conf`	Online Resource Allocation with Matching Constraints. AAMAS John P. Dickerson, Karthik Abinav Sankararaman, Kanthi Kiran Sarpatwar, Aravind Srinivasan, Kun-Lung Wu, Pan Xu
2019	—	`—`	Sequential Decision Making with Limited Resources. Karthik Abinav Sankararaman
2019	A	`conf`	Stability of Linear Structural Equation Models of Causal Inference. UAI Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
2019	J	`jnl`	Stability of Linear Structural Equation Models of Causal Inference. CoRR Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
2019	J	`jnl`	The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. CoRR Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein
2018	J	`jnl`	Adversarial Bandits with Knapsacks. CoRR Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2018	A*	`conf`	Algorithms to Approximate Column-Sparse Packing Problems. SODA Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018	A*	`conf`	Allocation Problems in Ride-Sharing Platforms: Online Matching With Offline Reusable Resources. AAAI John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018	A	`conf`	Assigning Tasks to Workers based on Historical Data: Online Task Assignment with Two-sided Arrivals. AAMAS John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018	J	`jnl`	Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts. CoRR Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018	J	`jnl`	Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. CoRR John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018	A	`conf`	Combinatorial Semi-Bandits with Knapsacks. AISTATS Karthik Abinav Sankararaman, Aleksandrs Slivkins
2017	J	`jnl`	Algorithms to Approximate Column-Sparse Packing Problems. CoRR Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2017	J	`jnl`	Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources. CoRR John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2017	A	`conf`	Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts. AAMAS Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2017	J	`jnl`	Semi-Bandits with Knapsacks. CoRR Karthik Abinav Sankararaman, Aleksandrs Slivkins
2016	A	`conf`	New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching. ESA Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2016	J	`jnl`	New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching. CoRR Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2014	—	`conf`	Ensuring Privacy in Location-Based Services: An Approach Based on Opacity Enforcement. WODES Yi-Chin Wu, Karthik Abinav Sankararaman, Stéphane Lafortune