
CS PhD student at @UCSanDiego, Intern at @Livermore_Lab | Prev. @SonyAI_global, @val_iisc, @teamIvLabs
La Jolla, California
Joined December 2014
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Akshay Kulkarni retweeted
📣Thrilled that "Rethinking Dataset Distillation: Hard Truths about Soft Labels" is a Best Paper Finalist @CVPR (Top 15 out of 16,000+ submissions)! 🏆
Congrats to the authors! 🥳🙌🏻
Join us today:
🎙️ Oral: 10:15 @ Mile High Ballroom 1A-2A
📍Poster 18 @ ExHall A
Excited to share that our paper on Concept Bottleneck Sparse Autoencoders (CB-SAE) will be presented at CVPR 2026 tomorrow!
CB-SAE combines sparse autoencoders (SAEs) with concept bottlenecks to make multimodal LLMs more interpretable and steerable.
This work was done during my internship at LLNL. I’m grateful to @kowshik0808 and Vivek Narayanaswamy for the opportunity and guidance during the internship. Many thanks also to my PhD advisor @LilyWeng_ and co-authors Shusen Liu and Wesam Sakla for their help on this project.
Check out this press release by LLNL: computing.llnl.gov/about/new…
Please stop by if you’re attending CVPR, would love to discuss interpretability, sparse autoencoders, and concept bottleneck models!
#CVPR2026 #Interpretability #ExplainableAI #SparseAutoencoders #ConceptBottlenecks
Akshay Kulkarni retweeted
🧵HOW speaker spotlight @CVPR !
Right after we have Prof. @LilyWeng_ from @UCSD
"Toward a Science of Interpretability: Structured Explanations and Reliable Evaluation" - principled, rigorous approaches to understanding neural nets
📅 June 4 @ Room 1Ef | 2:30–3:00 PM
🧵HOW speaker spotlight @CVPR !
The afternoon sessions starts with Prof. Alexei "Alyosha" Efros from @UCBerkeley who will be joining us to share his perspective on current vision models and their internals.
📅 June 4 @ Room 1Ef | 2:30–3:00 PM
Honored to be recognized as an Outstanding Reviewer at CVPR 2026!
We are grateful to all of the 17,491 reviewers who helped make #CVPR2026 possible. We are especially pleased to recognize the following Outstanding Reviewers, whose high-quality reviews (as judged by their Area Chairs) placed them among the top 5% of reviewers.
We are grateful to all of the 17,491 reviewers who helped make #CVPR2026 possible. We are especially pleased to recognize the following Outstanding Reviewers, whose high-quality reviews (as judged by their Area Chairs) placed them among the top 5% of reviewers.
Akshay Kulkarni retweeted
Excited to share that I'll be at #NeurIPS2025 from Dec 2-7, presenting two of my works 🚀
1. LLM Agent Safety Against Prompt Injections
2. Anomaly Detection Using VLMs
I’m looking for PhD positions starting Fall 2026.
Happy to connect, feel free to DM :)
Poster details in 🧵
Akshay Kulkarni retweeted
🚨 New Paper Alert!
🚀 Excited to introduce CAVE: A benchmark for detecting and explaining commonsense anomalies in real-world visual environments!
Accepted at #EMNLP2025 Main Conference! 🎉
📍Join us at our poster on Nov 5, 16:30-18:00 in Hall C.
Akshay Kulkarni retweeted
Are Firewalls All You Need, or Stronger Benchmarks?
Benchmarking is critical for understanding and comparing the security of tool-calling agents. As attacks evolve and defenses adapt, researchers need consistent, realistic, and reproducible evaluation frameworks to identify true progress and avoid misleading conclusions. Several recent benchmarks, such as AgentDojo, Agent Security Bench, and InjecAgent, aim to simulate real-world attack scenarios.
However, our analysis further reveals that many of these benchmarks do not model real-world situations appropriately and sometimes employ skewed metrics to gauge performance. In such cases, even weak defenses may seem deceptively effective.
We highlight these limitations and fix them through our proposed standardized benchmarking best-practices.
Source: arxiv.org/pdf/2510.05244
@rishika2110, @KevinKasa98, @AbhayPuri98, @GabrielHuang9, @irinarish, Graham W. Taylor, @DjDvij, @alex_lacoste_ - @ServiceNowRSRCH, @Mila_Quebec, @UMontreal, @VectorInst, @uofg
#PromptInjection #LLMSecurity #AIAgents #AgentSecurity #AIEvaluation #Guardrails #CyberSecurity #AISafety #MilaQuebec #ServiceNowResearch #VectorInstitute #UniversityOfGuelph
⚡Interested in making pretrained generative models interpretable with minimal training and annotations?
I'll be presenting our paper, Interpretable Generative Models through Post-hoc Concept Bottlenecks, at #CVPR2025 today in Poster Session 2 (4 pm - 6 pm CDT) at poster #266!
🚀 Paper: arxiv.org/abs/2503.19377
🚀 Code: github.com/Trustworthy-ML-La…
🚀 Project site: lilywenglab.github.io/postho…
Thanks to my co-authors, Ge Yan, @sun_chung_en, @tuomasoi, and my PhD advisor @LilyWeng_
















