← Authors

Bhavya Kailkhura

44 papers · 2018–2026 · 13 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (13) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (75) πŸ† Grand Slam 🀝 Dynamic Duo (11) πŸ‘₯ Mega-Team (71) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) 🧬 Topic Evolution ⚑ Prolific Year (14) πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (43) ❓ The Questioner (3) πŸ—ƒοΈ Keyword Collector (181)

Conferences

NIPS (11) ICLR (6) ICML (5) NAACL (4) ACL (3) ICCV (3) AAAI (2) CVPR (2) ECCV (2) JMLR (2) WACV (2) EMNLP (1) UAI (1)

Top co-authors

James Diffenderfer (11) Brian R. Bartoldson (8) Kaidi Xu (8) Bo Li (7) Pin-Yu Chen (6) Tianlong Chen (5) Jinhao Duan (5) Sijia Liu (4) Lichao Sun (4) Akshay Mehra (4)

Keywords

large language model (5) domain generalization (3) zeroth-order optimization (2) spectral analysis (2) adversarial robustness (2) domain shift (2) model unlearning (2) model robustness (2) out-of-distribution generalization (2) certified robustness (2) adversarial training (2) image classification (2) foundation model (2) data poisoning (2) strategic reasoning (2) adversarial learning (2) representation learning (2) data augmentation (2) neural network optimization (2) board game (2)

Papers

STAR-1: Safer Alignment of Reasoning LLMs with 1K Data AAAI 2026
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense NAACL 2025
GRNFormer: A Biologically-Guided Framework for Integrating Gene Regulatory Networks into RNA Foundation Models ACL 2025
Extracting and Understanding the Superficial Knowledge in Alignment NAACL 2025
ELFS: Label-Free Coreset Selection with Proxy Training Dynamics ICLR 2025
TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention ICCV 2025
Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion NAACL 2025
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training ICLR 2024
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations NIPS 2024
Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis NIPS 2024
Transformers Can Do Arithmetic with the Right Embeddings NIPS 2024
Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models ACL 2024
RankMean: Module-Level Importance Score for Merging Fine-tuned LLM Models ACL 2024
Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation ECCV 2024
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning EMNLP 2024
NEFTune: Noisy Embeddings Improve Instruction Finetuning ICLR 2024
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies ICML 2024
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression ICML 2024
Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models NAACL 2024
On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization WACV 2024
Improving Diversity With Adversarially Learned Transformations for Domain Generalization WACV 2023
Neural Image Compression: Generalization, Robustness, and Spectral Biases NIPS 2023
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities JMLR 2023
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks ICLR 2022
On the Certified Robustness for Ensemble Models and Beyond ICLR 2022
Models Out of Line: A Fourier Lens on Distribution Shift Robustness NIPS 2022
A Spectral View of Randomized Smoothing under Common Corruptions: Benchmarking and Improving Certified Robustness ECCV 2022
Can Shape Structure Features Improve Model Robustness Under Diverse Adversarial Settings? ICCV 2021
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network ICLR 2021
A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness NIPS 2021
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning NIPS 2021
Deep kernels with probabilistic embeddings for small-data learning UAI 2021
Attribute-Guided Adversarial Training for Robustness to Natural Perturbations AAAI 2021
How Robust Are Randomized Smoothing Based Defenses to Data Poisoning? CVPR 2021
Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators NIPS 2021
A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning NIPS 2020
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond NIPS 2020
Adversarial Mutual Information for Text Generation ICML 2020
Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning ICML 2020
On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method ICCV 2019
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization NIPS 2018
A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms JMLR 2018