Arun Verma

59 papers A* 11A 2B 1C 1Misc 3Journal 35Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
BarrierSteer: LLM Safety via Learning Barrier Steering.
CoRR
Thanh Q. Tran, Arun Verma, Kiwan Wong, Bryan Kian Hsiang Low, Daniela Rus, Wei Xiao
2026 J jnl
MineDraft: A Framework for Batch Parallel Speculative Decoding.
CoRR
Zhenwei Tang, Arun Verma, Zijian Zhou, Zhaoxuan Wu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2026 Misc conf
Stochastic Multi-Armed Bandits with Limited Control Variates.
COMSNETS
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar
2026 J jnl
Stochastic Multi-Armed Bandits with Limited Control Variates.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar
2025 J jnl
Active Human Feedback Collection via Neural Contextual Dueling Bandits.
CoRR
Arun Verma, Xiaoqiang Lin, Zhongxiang Dai, Daniela Rus, Bryan Kian Hsiang Low
2025 J jnl
ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment.
CoRR
Xiaoqiang Lin, Arun Verma, Zhongxiang Dai, Daniela Rus, See-Kiong Ng, Bryan Kian Hsiang Low
2025 J jnl
COBRA: Contextual Bandit Algorithm for Ensuring Truthful Strategic Agents.
CoRR
Arun Verma, Indrajit Saha, Makoto Yokoo, Bryan Kian Hsiang Low
2025 J jnl
Incentivizing Time-Aware Fairness in Data Sharing.
CoRR
Jiangwei Chen, Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Arun Verma, Zhaoxuan Wu, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025 A* conf
Neural Dueling Bandits: Preference-Based Optimization with Human Feedback.
ICLR
Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
2025 — conf
TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding.
ACL (1)
Zhaoxuan Wu, Zijian Zhou, Arun Verma, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2025 J jnl
TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding.
CoRR
Zhaoxuan Wu, Zijian Zhou, Arun Verma, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2025 — conf
Uncovering Scaling Laws for Large Language Models via Inverse Problems.
EMNLP (Findings)
Arun Verma, Zhaoxuan Wu, Zijian Zhou, Xiaoqiang Lin, Zhiliang Chen, Rachael Hwee Ling Sim, Rui Qiao, Jingtan Wang, Nhung Bui, Xinyuan Niu, Wenyang Hu, Gregory Kang Ruey Lau, Zi-Yu Khoo, Zitong Zhao, Xinyi Xu, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
2025 J jnl
Uncovering Scaling Laws for Large Language Models via Inverse Problems.
CoRR
Arun Verma, Zhaoxuan Wu, Zijian Zhou, Xiaoqiang Lin, Zhiliang Chen, Rachael Hwee Ling Sim, Rui Qiao, Jingtan Wang, Nhung Bui, Xinyuan Niu, Wenyang Hu, Gregory Kang Ruey Lau, Zi-Yu Khoo, Zitong Zhao, Xinyi Xu, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
2024 J jnl
Data-Centric AI in the Age of Large Language Models.
CoRR
Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
2024 J jnl
Neural Dueling Bandits.
CoRR
Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
2024 J jnl
Online Fair Division with Contextual Bandits.
CoRR
Arun Verma, Indrajit Saha, Makoto Yokoo, Bryan Kian Hsiang Low
2024 — conf
Position Paper: Data-Centric AI in the Age of Large Language Models.
EMNLP (Findings)
Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
2024 J jnl
Prompt Optimization with Human Feedback.
CoRR
Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2024 J jnl
Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models.
CoRR
Ze Yu Zhang, Arun Verma, Finale Doshi-Velez, Bryan Kian Hsiang Low
2023 A* conf
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits.
NeurIPS
Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low
2023 J jnl
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits.
CoRR
Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low
2023 A conf
FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery.
AISTATS
Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low
2023 A* conf
Federated Neural Bandits.
ICLR
Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet
2023 A* conf
Quantum Bayesian Optimization.
NeurIPS
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
2023 J jnl
Quantum Bayesian Optimization.
CoRR
Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet
2023 A* conf
Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation.
ICLR
Thanh Lam, Arun Verma, Bryan Kian Hsiang Low, Patrick Jaillet
2023 A* conf
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation.
ICLR
Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low
2022 J jnl
Application of Clustering Algorithms for Dimensionality Reduction in Infrastructure Resilience Prediction Models.
CoRR
Srijith Balakrishnan, Beatrice Cassottana, Arun Verma
2022 A* conf
Bayesian Optimization under Stochastic Delayed Feedback.
ICML
Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low
2022 J jnl
Bayesian Optimization under Stochastic Delayed Feedback.
CoRR
Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low
2022 J jnl
Federated Neural Bandit.
CoRR
Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet
2022 J jnl
Sequential Decision Problems with Weak Feedback.
CoRR
Arun Verma
2021 J jnl
Censored Semi-Bandits for Resource Allocation.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran
2021 A* conf
Stochastic Multi-Armed Bandits with Control Variates.
NeurIPS
Arun Verma, Manjesh Kumar Hanawal
2021 J jnl
Stochastic Multi-Armed Bandits with Control Variates.
CoRR
Arun Verma, Manjesh Kumar Hanawal
2020 — conf
Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach.
SPCOM
Debamita Ghosh, Arun Verma, Manjesh Kumar Hanawal
2020 J jnl
Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach.
CoRR
Debamita Ghosh, Arun Verma, Manjesh Kumar Hanawal
2020 A* conf
Online Algorithm for Unsupervised Sequential Selection with Contextual Information.
NeurIPS
Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama
2020 J jnl
Online Algorithm for Unsupervised Sequential Selection with Contextual Information.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama
2020 A* conf
Stochastic Network Utility Maximization with Unknown Utilities: Multi-Armed Bandits Approach.
INFOCOM
Arun Verma, Manjesh Kumar Hanawal
2020 J jnl
Stochastic Network Utility Maximization with Unknown Utilities: Multi-Armed Bandits Approach.
CoRR
Arun Verma, Manjesh Kumar Hanawal
2020 C conf
Thompson Sampling for Unsupervised Sequential Selection.
ACML
Arun Verma, Manjesh Kumar Hanawal, Nandyala Hemachandra
2020 J jnl
Thompson Sampling for Unsupervised Sequential Selection.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Nandyala Hemachandra
2020 Misc conf
Unsupervised Online Feature Selection for Cost-Sensitive Medical Diagnosis.
COMSNETS
Arun Verma, Manjesh Kumar Hanawal, Nandyala Hemachandra
2020 J jnl
Unsupervised Online Feature Selection for Cost-Sensitive Medical Diagnosis.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Nandyala Hemachandra
2019 A* conf
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback.
NeurIPS
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran
2019 J jnl
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran
2019 B conf
Distributed Algorithms for Efficient Learning and Coordination in Ad Hoc Networks.
WiOpt
Arun Verma, Manjesh Kumar Hanawal, Rahul Vaze
2019 A conf
Online Algorithm for Unsupervised Sensor Selection.
AISTATS
Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama
2019 J jnl
Online Algorithm for Unsupervised Sensor Selection.
CoRR
Arun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama
2019 Misc conf
Visual Attention Model for Cross-Sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning.
FLAIRS
Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent
2018 — conf
Unsupervised cost sensitive predictions with side information.
COMAD/CODS
Arun Verma, Manjesh Kumar Hanawal
2018 J jnl
Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning.
CoRR
Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent
2015 J jnl
Benchmarking Fast Data Platforms for the Aadhaar Biometric Database.
CoRR
Yogesh Simmhan, Anshu Shukla, Arun Verma
2015 — conf
Benchmarking Fast-Data Platforms for the Aadhaar Biometric Database.
WBDB
Yogesh L. Simmhan, Anshu Shukla, Arun Verma
2001 J jnl
A Preconditioned Conjugate Gradient Approach to Linear Equality Constrained Minimization.
Comput. Optim. Appl.
Thomas F. Coleman, Arun Verma
2000 J jnl
ADMIT-1: automatic differentiation and MATLAB interface toolbox.
ACM Trans. Math. Softw.
Thomas F. Coleman, Arun Verma
2000 J jnl
On Efficient Solutions to the Continuous Sensitivity Equation Using Automatic Differentiation.
SIAM J. Sci. Comput.
Jeff Borggaard, Arun Verma
1998 J jnl
The Efficient Computation of Sparse Jacobian Matrices Using Automatic Differentiation.
SIAM J. Sci. Comput.
Thomas F. Coleman, Arun Verma