New closed-form bounds on the partition function. - Krishnamurthy Dvijotham; Soumen Chakrabarti; Subhasis Chaudhuri (Mach. Learn., 2008)

A nullspace analysis of the nuclear norm heuristic for rank minimization. - Krishnamurthy Dvijotham; Maryam Fazel (ICASSP, 2010)

Inverse Optimal Control with Linearly-Solvable MDPs. - Krishnamurthy Dvijotham; Emanuel Todorov (ICML, 2010)

A Unifying Framework for Linearly Solvable Control. - Krishnamurthy Dvijotham; Emanuel Todorov (UAI, 2011)

Operations-Based Planning for Placement and Sizing of Energy Storage in a Grid With a High Penetration of Renewables - Krishnamurthy Dvijotham; Scott Backhaus; Misha Chertkov (CoRR, 2011)

Linearly solvable Markov games. - Krishnamurthy Dvijotham; Emo Todorov (ACC, 2012)

Distributed control of generation in a transmission grid with a high penetration of renewables. - Krishnamurthy Dvijotham; Scott Backhaus; Michael Chertkov (SmartGridComm, 2012)

Convex control design via covariance minimization. - Krishnamurthy Dvijotham; Emanuel Todorov; Maryam Fazel (Allerton, 2013)

Convexity of optimal linear controller design. - Krishnamurthy Dvijotham; Evangelos A. Theodorou; Emanuel Todorov; Maryam Fazel (CDC, 2013)

Time varying nonlinear Policy Gradients. - Evangelos A. Theodorou; Krishnamurthy Dvijotham; Emo Todorov (CDC, 2013)

Convex Structured Controller Design. - Krishnamurthy Dvijotham; Emanuel Todorov; Maryam Fazel (CoRR, 2013)

Convex risk averse control design. - Krishnamurthy Dvijotham; Maryam Fazel; Emanuel Todorov (CDC, 2014)

Storage Sizing and Placement through Operational and Uncertainty-Aware Simulations. - Krishnamurthy Dvijotham; Misha Chertkov; Scott Backhaus (HICSS, 2014)

Universal Convexification via Risk-Aversion. - Krishnamurthy Dvijotham; Maryam Fazel; Emanuel Todorov (UAI, 2014)

Efficient Synchronization Stability Metrics for Fault Clearing. - Scott Backhaus; Russell Bent; Daniel Bienstock; Michael Chertkov; Krishnamurthy Dvijotham (CoRR, 2014)

Automating Stochastic Optimal Control. - Krishnamurthy Dvijotham (2014)

Systems of quadratic equations: Efficient solution algorithms and conditions for solvability. - Krishnamurthy Dvijotham (Allerton, 2015)

Convexity of structure preserving energy functions in power transmission: Novel results and applications. - Krishnamurthy Dvijotham; Michael Chertkov (ACC, 2015)

A differential analysis of the power flow equations. - Krishnamurthy Dvijotham; Michael Chertkov; Steven H. Low (CDC, 2015)

Solving the Power Flow Equations: A Monotone Operator Theory Approach. - Krishnamurthy Dvijotham; Michael Chertkov; Steven H. Low (CoRR, 2015)

Solving the Power Flow Equations: A Monotone Operator Approach. - Krishnamurthy Dvijotham; Steven H. Low; Michael Chertkov (CoRR, 2015)

Construction of power flow feasibility sets. - Krishnamurthy Dvijotham; Konstantin S. Turitsyn (CoRR, 2015)

Natural Gas Flow Solutions with Guarantees: A Monotone Operator Theory Approach. - Krishnamurthy Dvijotham; Marc Vuffray; Sidhant Misra; Michael Chertkov (CoRR, 2015)

Convex Structured Controller Design in Finite Horizon. - Krishnamurthy Dvijotham; Emanuel Todorov; Maryam Fazel (IEEE Trans. Control. Netw. Syst., 2015)

Monotone operator approach to power flow solutions. - Krishnamurthy Dvijotham; Michael Chertkov; Steven H. Low (ACC, 2016)

Error bounds on the DC power flow approximation: A convex relaxation approach. - Krishnamurthy Dvijotham; Daniel K. Molzahn (CDC, 2016)

Market Dynamics of Best-Response with Lookahead. - Krishnamurthy Dvijotham; Yuval Rabani; Leonard J. Schulman (CoRR, 2016)

Opportunities for Price Manipulation by Aggregators in Electricity Markets. - Navid Azizan Ruhi; Niangjun Chen; Krishnamurthy Dvijotham; Adam Wierman (SIGMETRICS Perform. Evaluation Rev., 2016)

Real-time OPF based on quasi-Newton methods. - Yujie Tang 002; Krishnamurthy Dvijotham; Steven H. Low (CISS, 2017)

Graphical models for optimal power flow. - Krishnamurthy Dvijotham; Michael Chertkov; Pascal Van Hentenryck; Marc Vuffray; Sidhant Misra (Constraints An Int. J., 2017)

High-Voltage Solution in Radial Power Networks: Existence, Properties, and Equivalent Algorithms. - Krishnamurthy Dvijotham; Enrique Mallada; John W. Simpson-Porco (IEEE Control. Syst. Lett., 2017)

Real-Time Optimal Power Flow. - Yujie Tang 002; Krishnamurthy Dvijotham; Steven H. Low (IEEE Trans. Smart Grid, 2017)

A Dual Approach to Scalable Verification of Deep Networks. - Krishnamurthy Dvijotham; Robert Stanforth; Sven Gowal; Timothy A. Mann; Pushmeet Kohli (UAI, 2018)

Learning Fast Optimizers for Contextual Stochastic Integer Programs. - Vinod Nair; Dj Dvijotham; Iain Dunning; Oriol Vinyals (UAI, 2018)

Safe Exploration in Continuous Action Spaces. - Gal Dalal; Krishnamurthy Dvijotham; Matej Vecerík; Todd Hester; Cosmin Paduraru; Yuval Tassa (CoRR, 2018)

Training verified learners with learned verifiers. - Krishnamurthy Dvijotham; Sven Gowal; Robert Stanforth; Relja Arandjelovic; Brendan O'Donoghue; Jonathan Uesato; Pushmeet Kohli (CoRR, 2018)

On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models. - Sven Gowal; Krishnamurthy Dvijotham; Robert Stanforth; Rudy Bunel; Chongli Qin; Jonathan Uesato; Relja Arandjelovic; Timothy A. Mann; Pushmeet Kohli (CoRR, 2018)

Verification of deep probabilistic models. - Krishnamurthy Dvijotham; Marta Garnelo; Alhussein Fawzi; Pushmeet Kohli (CoRR, 2018)

Solvability Regions of Affinely Parameterized Quadratic Equations. - Krishnamurthy Dvijotham; Hung D. Nguyen 001; Konstantin S. Turitsyn (IEEE Control. Syst. Lett., 2018)

Knowing When to Stop: Evaluation and Verification of Conformity to Output-Size Specifications. - Chenglong Wang; Rudy Bunel; Krishnamurthy Dvijotham; Po-Sen Huang; Edward Grefenstette; Pushmeet Kohli (CVPR, 2019)

Optimal Pricing in Markets with Non-Convex Costs. - Navid Azizan Ruhi; Yu Su 013; Krishnamurthy Dvijotham; Adam Wierman (EC, 2019)

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. - Po-Sen Huang; Robert Stanforth; Johannes Welbl; Chris Dyer; Dani Yogatama; Sven Gowal; Krishnamurthy Dvijotham; Pushmeet Kohli (EMNLP/IJCNLP (1), 2019)

Scalable Verified Training for Provably Robust Image Classification. - Sven Gowal; Krishnamurthy Dvijotham; Robert Stanforth; Rudy Bunel; Chongli Qin; Jonathan Uesato; Relja Arandjelovic; Timothy Arthur Mann; Pushmeet Kohli (ICCV, 2019)

Verification of Non-Linear Specifications for Neural Networks. - Chongli Qin; Krishnamurthy (Dj) Dvijotham; Brendan O'Donoghue; Rudy Bunel; Robert Stanforth; Sven Gowal; Jonathan Uesato; Grzegorz Swirszcz; Pushmeet Kohli (ICLR (Poster), 2019)

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures. - Jonathan Uesato; Ananya Kumar; Csaba Szepesvári; Tom Erez; Avraham Ruderman; Keith Anderson; Krishnamurthy (Dj) Dvijotham; Nicolas Heess; Pushmeet Kohli (ICLR (Poster), 2019)

A Dual Approach to Verify and Train Deep Networks. - Sven Gowal; Krishnamurthy Dvijotham; Robert Stanforth; Timothy A. Mann; Pushmeet Kohli (IJCAI, 2019)

Adversarial Robustness through Local Linearization. - Chongli Qin; James Martens; Sven Gowal; Dilip Krishnan; Krishnamurthy Dvijotham; Alhussein Fawzi; Soham De; Robert Stanforth; Pushmeet Kohli (NeurIPS, 2019)

Efficient Neural Network Verification with Exactness Characterization. - Krishnamurthy (Dj) Dvijotham; Robert Stanforth; Sven Gowal; Chongli Qin; Soham De; Pushmeet Kohli (UAI, 2019)

Convex Restriction of Power Flow Feasibility Sets. - Dongchan Lee; Hung D. Nguyen 001; Krishnamurthy Dvijotham; Konstantin S. Turitsyn (IEEE Trans. Control. Netw. Syst., 2019)

A Framework for Robust Long-Term Voltage Stability of Distribution Systems. - Hung D. Nguyen 001; Krishnamurthy Dvijotham; Suhyoun Yu; Konstantin S. Turitsyn (IEEE Trans. Smart Grid, 2019)

Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations. - Sven Gowal; Chongli Qin; Po-Sen Huang; A. Taylan Cemgil; Krishnamurthy Dvijotham; Timothy A. Mann; Pushmeet Kohli (CVPR, 2020)

Adversarially Robust Representations with Smooth Encoders. - A. Taylan Cemgil; Sumedh Ghaisas; Krishnamurthy (Dj) Dvijotham; Pushmeet Kohli (ICLR, 2020)

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences. - Krishnamurthy (Dj) Dvijotham; Jamie Hayes; Borja Balle; J. Zico Kolter; Chongli Qin; András György 001; Kai Xiao; Sven Gowal; Pushmeet Kohli (ICLR, 2020)

Towards Verified Robustness under Text Deletion Interventions. - Johannes Welbl; Po-Sen Huang; Robert Stanforth; Sven Gowal; Krishnamurthy (Dj) Dvijotham; Martin Szummer; Pushmeet Kohli (ICLR, 2020)

Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control. - Tsui-Wei Weng; Krishnamurthy (Dj) Dvijotham; Jonathan Uesato; Kai Xiao; Sven Gowal; Robert Stanforth; Pushmeet Kohli (ICLR, 2020)

The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver. - Anton Zhernov; Krishnamurthy (Dj) Dvijotham; Ivan Lobov; Dan A. Calian; Michelle X. Gong; Natarajan Chandrashekar; Timothy A. Mann (KDD, 2020)

An efficient nonconvex reformulation of stagewise convex optimization problems. - Rudy Bunel; Oliver Hinder; Srinadh Bhojanapalli; Krishnamurthy Dvijotham (NeurIPS, 2020)

The Autoencoding Variational Autoencoder. - A. Taylan Cemgil; Sumedh Ghaisas; Krishnamurthy Dvijotham; Sven Gowal; Pushmeet Kohli (NeurIPS, 2020)

Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. - Sumanth Dathathri; Krishnamurthy Dvijotham; Alexey Kurakin; Aditi Raghunathan; Jonathan Uesato; Rudy Bunel; Shreya Shankar; Jacob Steinhardt; Ian J. Goodfellow; Percy Liang; Pushmeet Kohli (NeurIPS, 2020)

Lagrangian Decomposition for Neural Network Verification. - Rudy Bunel; Alessandro De Palma; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (UAI, 2020)

Towards transformation-resilient provenance detection of digital media. - Jamie Hayes; Krishnamurthy Dvijotham; Yutian Chen; Sander Dieleman; Pushmeet Kohli; Norman Casagrande (CoRR, 2020)

Optimal Pricing in Markets with Nonconvex Costs. - Navid Azizan; Yu Su 013; Krishnamurthy Dvijotham; Adam Wierman (Oper. Res., 2020)

Overcoming the Convex Barrier for Simplex Inputs. - Harkirat Singh Behl; M. Pawan Kumar; Philip H. S. Torr; Krishnamurthy Dvijotham (NeurIPS, 2021)

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications. - Leonard Berrada; Sumanth Dathathri; Krishnamurthy Dvijotham; Robert Stanforth; Rudy Bunel; Jonathan Uesato; Sven Gowal; M. Pawan Kumar (NeurIPS, 2021)

Verifying Probabilistic Specifications with Functional Lagrangians. - Leonard Berrada; Sumanth Dathathri; Krishnamurthy Dvijotham; Robert Stanforth; Rudy Bunel; Jonathan Uesato; Sven Gowal; M. Pawan Kumar (CoRR, 2021)

Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. - Alessandro De Palma; Rudy Bunel; Alban Desmaison; Krishnamurthy Dvijotham; Pushmeet Kohli; Philip H. S. Torr; M. Pawan Kumar (CoRR, 2021)

Robust Optimization for Electricity Generation. - Haoxiang Yang; David P. Morton; Chaithanya Bandi; Krishnamurthy Dvijotham (INFORMS J. Comput., 2021)

Role of Human-AI Interaction in Selective Prediction. - Elizabeth Bondi; Raphael Koster; Hannah Sheahan; Martin J. Chadwick; Yoram Bachrach; A. Taylan Cemgil; Ulrich Paquet; Krishnamurthy Dvijotham (AAAI, 2022)

Learning Optimal Conformal Classifiers. - David Stutz; Krishnamurthy Dvijotham; Ali Taylan Cemgil; Arnaud Doucet (ICLR, 2022)

A Fine-Grained Analysis on Distribution Shift. - Olivia Wiles; Sven Gowal; Florian Stimberg; Sylvestre-Alvise Rebuffi; Ira Ktena; Krishnamurthy Dvijotham; Ali Taylan Cemgil (ICLR, 2022)

(Certified!!) Adversarial Robustness for Free! - Nicholas Carlini; Florian Tramèr; Krishnamurthy Dvijotham; J. Zico Kolter (CoRR, 2022)

IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound. - Alessandro De Palma; Rudy Bunel; Krishnamurthy Dvijotham; M. Pawan Kumar; Robert Stanforth (CoRR, 2022)

Convergence of incentive-driven dynamics in Fisher markets. - Krishnamurthy Dvijotham; Yuval Rabani; Leonard J. Schulman (Games Econ. Behav., 2022)

Fixed-Point Theorem-Based Voltage Stability Margin Estimation Techniques for Distribution Systems With Renewables. - Yu Weng; Suhyoun Yu; Krishnamurthy Dvijotham; Hung D. Nguyen 001 (IEEE Trans. Ind. Informatics, 2022)

Interactive Concept Bottleneck Models. - Kushal Chauhan; Rishabh Tiwari; Jan Freyberg; Pradeep Shenoy; Krishnamurthy Dvijotham (AAAI, 2023)

Human Uncertainty in Concept-Based AI Systems. - Katherine Maeve Collins; Matthew Barker; Mateo Espinosa Zarlenga; Naveen Raman 001; Umang Bhatt; Mateja Jamnik; Ilia Sucholutsky; Adrian Weller; Krishnamurthy Dvijotham (AIES, 2023)

(Certified!!) Adversarial Robustness for Free! - Nicholas Carlini; Florian Tramèr; Krishnamurthy (Dj) Dvijotham; Leslie Rice; Mingjie Sun; J. Zico Kolter (ICLR, 2023)

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. - Jeremiah Zhe Liu; Krishnamurthy (Dj) Dvijotham; Jihyeon Lee; Quan Yuan 001; Balaji Lakshminarayanan; Deepak Ramachandran (ICLR, 2023)

Provably Bounding Neural Network Preimages. - Suhas Kotha; Christopher Brix; J. Zico Kolter; Krishnamurthy Dvijotham; Huan Zhang 001 (NeurIPS, 2023)

Training Private Models That Know What They Don't Know. - Stephan Rabanser; Anvith Thudi; Abhradeep Guha Thakurta; Krishnamurthy Dvijotham; Nicolas Papernot (NeurIPS, 2023)

Learning to Receive Help: Intervention-Aware Concept Embedding Models. - Mateo Espinosa Zarlenga; Katie Collins; Krishnamurthy Dvijotham; Adrian Weller; Zohreh Shams; Mateja Jamnik (NeurIPS, 2023)

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. - Jeremiah Zhe Liu; Krishnamurthy (Dj) Dvijotham; Jihyeon Lee; Quan Yuan 001; Martin Strobel 001; Balaji Lakshminarayanan; Deepak Ramachandran (CoRR, 2023)

Efficient Symbolic Reasoning for Neural-Network Verification. - Zi Wang; Somesh Jha; Krishnamurthy Dvijotham (CoRR, 2023)

Provably Correct Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; Philip H. S. Torr; M. Pawan Kumar (CoRR, 2023)

Faithful Knowledge Distillation. - Tom A. Lamb; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; M. Pawan Kumar; Philip H. S. Torr; Francisco Eiras (CoRR, 2023)

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time. - Matthew Barker; Katherine M. Collins; Krishnamurthy Dvijotham; Adrian Weller; Umang Bhatt (CoRR, 2023)

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. - Jacob Eisenstein; Chirag Nagpal; Alekh Agarwal; Ahmad Beirami; Alex D'Amour; Dj Dvijotham; Adam Fisch; Katherine A. Heller; Stephen Pfohl; Deepak Ramachandran; Peter Shaw 004; Jonathan Berant (CoRR, 2023)

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. - Katherine M. Collins; Najoung Kim; Yonatan Bitton; Verena Rieser; Shayegan Omidshafiei; Yushi Hu; Sherol Chen; Senjuti Dutta; Minsuk Chang; Kimin Lee; Youwei Liang; Georgina Evans; et al. (AIES (1), 2024)

Rich Human Feedback for Text-to-Image Generation. - Youwei Liang; Junfeng He; Gang Li; Peizhao Li; Arseniy Klimovskiy; Nicholas Carolan; Jiao Sun; Jordi Pont-Tuset; Sarah Young; Feng Yang; Junjie Ke; Krishnamurthy Dj Dvijotham; et al. (CVPR, 2024)

Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy. - Krishnamurthy Dj Dvijotham; H. Brendan McMahan; Krishna Pillutla; Thomas Steinke 001; Abhradeep Thakurta (FOCS, 2024)

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning. - Christopher A. Choquette-Choo; Krishnamurthy Dj Dvijotham; Krishna Pillutla; Arun Ganesh; Thomas Steinke 002; Abhradeep Guha Thakurta (ICLR, 2024)

Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. - Kyuyoung Kim; Jongheon Jeong; Minyong An; Mohammad Ghavamzadeh; Krishnamurthy Dj Dvijotham; Jinwoo Shin; Kimin Lee (ICLR, 2024)

Expressive Losses for Verified Robustness via Convex Combinations. - Alessandro De Palma; Rudy Bunel; Krishnamurthy (Dj) Dvijotham; M. Pawan Kumar; Robert Stanforth; Alessio Lomuscio (ICLR, 2024)

Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation. - Gavin Brown 003; Krishnamurthy Dj Dvijotham; Georgina Evans; Daogao Liu; Adam Smith 006; Abhradeep Guha Thakurta (ICML, 2024)

Stealing part of a production language model. - Nicholas Carlini; Daniel Paleka; Krishnamurthy Dj Dvijotham; Thomas Steinke 002; Jonathan Hayase; A. Feder Cooper; Katherine Lee; Matthew Jagielski; Milad Nasr; Arthur Conmy; Eric Wallace; David Rolnick; et al. (ICML, 2024)

Efficient Error Certification for Physics-Informed Neural Networks. - Francisco Eiras; Adel Bibi; Rudy Bunel; Krishnamurthy Dj Dvijotham; Philip Torr 001; M. Pawan Kumar (ICML, 2024)

Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks. - Ruigang Wang; Krishnamurthy Dj Dvijotham; Ian R. Manchester (ICML, 2024)

MINT: A wrapper to make multi-modal and multi-image AI models interactive. - Jan Freyberg; Abhijit Guha Roy; Terry Spitz; Beverly Freeman; Mike Schaekermann; Patricia Strachan; Eva Schnider; Renee Wong; Dale R. Webster; Alan Karthikesalingam; Yun Liu 013; Krishnamurthy Dvijotham; et al. (CoRR, 2024)

Understanding Subjectivity through the Lens of Motivational Context in Model-Generated Image Satisfaction. - Senjuti Dutta; Sherol Chen; Sunny Mak; Amnah Ahmad; Katherine Maeve Collins; Alena Butryna; Deepak Ramachandran; Krishnamurthy Dvijotham; Ellie Pavlick; Ravi Rajakumar (CoRR, 2024)

Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy. - Krishnamurthy Dvijotham; H. Brendan McMahan; Krishna Pillutla; Thomas Steinke 002; Abhradeep Thakurta (CoRR, 2024)

Verified Neural Compressed Sensing. - Rudy Bunel; Krishnamurthy Dvijotham; M. Pawan Kumar; Alessandro De Palma; Robert Stanforth (CoRR, 2024)

Achieving the Tightest Relaxation of Sigmoids for Formal Verification. - Samuel Chevalier; Duncan Starkenburg; Krishnamurthy Dvijotham (CoRR, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

LLMs for Literature Review: Are we there yet? - Shubham Agarwal; Gaurav Sahu; Abhay Puri; Issam H. Laradji; Krishnamurthy Dj Dvijotham; Jason Stanley; Laurent Charlin; Christopher Pal (CoRR, 2024)

Robust feasibility of systems of quadratic equations using topological degree theory. - Krishnamurthy Dvijotham; Bala Krishnamoorthy; Yunqi Luo; Benjamin Rapone (Optim. Lett., 2024)

Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning. - Avinandan Bose; Laurent Lessard; Maryam Fazel; Krishnamurthy Dj Dvijotham (AISTATS, 2025)

LitLLMs, LLMs for Literature Review: Are we there yet? - Shubham Agarwal; Gaurav Sahu; Abhay Puri; Issam H. Laradji; Krishnamurthy Dj Dvijotham; Jason Stanley; Laurent Charlin; Christopher Pal (Trans. Mach. Learn. Res., 2025)

Norm-Bounded Low-Rank Adaptation. - Ruigang Wang; Krishnamurthy Dvijotham; Ian R. Manchester (CoRR, 2025)

Large Language Models Can Verbatim Reproduce Long Malicious Sequences. - Sharon Lin; Krishnamurthy Dvijotham; Jamie Hayes; Chongyang Shi 003; Ilia Shumailov; Shuang Song 001 (CoRR, 2025)

DoomArena: A framework for Testing AI Agents Against Evolving Security Threats. - Léo Boisvert; Mihir Bansal; Chandra Kiran Reddy Evuru; Gabriel Huang; Abhay Puri; Avinandan Bose; Maryam Fazel; Quentin Cappart; Jason Stanley; Alexandre Lacoste; Alexandre Drouin; Krishnamurthy Dvijotham (CoRR, 2025)

Through the Stealth Lens: Rethinking Attacks and Defenses in RAG. - Sarthak Choudhary; Nils Palumbo; Ashish Hooda; Krishnamurthy Dj Dvijotham; Somesh Jha (CoRR, 2025)

Correlated Noise Mechanisms for Differentially Private Learning. - Krishna Pillutla; Jalaj Upadhyay; Christopher A. Choquette-Choo; Krishnamurthy Dvijotham; Arun Ganesh; Monika Henzinger; Jonathan Katz; Ryan McKenna; H. Brendan McMahan; Keith Rush; Thomas Steinke 002; Abhradeep Thakurta (CoRR, 2025)

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion. - Frederick Shpilevskiy; Saiyue Lyu; Krishnamurthy Dj Dvijotham; Mathias Lécuyer; Pierre-André Noël (CoRR, 2025)