collaborators

5 papers

cs.AI2026

The Low Frequency Trap: Video Language Models Fail at Simple Event Bookkeeping

Sarvesh Baskar, Zikui Cai, Shayan Shabihi +5

Real-world video benchmarks provide broad coverage, but their fixed clips entangle event count, rate, duration, and visual complexity, making failure modes hard to isolate. While e…

cs.AI2026

SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?

Udari Madhushani Sehwag, Elaine Lau, Haniyeh Ehsani Oskouie +14

Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly physical validation. While ex…

cs.CL2025

Hold Onto That Thought: Assessing KV Cache Compression On Reasoning

Minghui Liu, Aadi Palnitkar, Tahseen Rabbani +9

Large language models (LLMs) have demonstrated remarkable performance on long-context tasks, but are often bottlenecked by memory constraints. Namely, the KV cache, which is used t…

cs.CY2025

PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach

Udari Madhushani Sehwag, Shayan Shabihi, Alex McAvoy +4

Recent advances in Large Language Models (LLMs) have sparked concerns over their potential to acquire and misuse dangerous or high-risk capabilities, posing frontier risks. Current…

cs.LG2025

AegisLLM: Scaling Agentic Systems for Self-Reflective Defense in LLM Security

Zikui Cai, Shayan Shabihi, Bang An +5

We introduce AegisLLM, a cooperative multi-agent defense against adversarial attacks and information leakage. In AegisLLM, a structured workflow of autonomous agents - orchestrator…