1 citations · 1 across the 11 of their papers we have counts for
11 papers
Workspace Topology as an Attack Vector in Agentic Coding Assistants
Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9
Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…
Adaptive Instruction Composition for Automated LLM Red-Teaming
Jesse Zymet, Andy Luo, Swapnil Shinde +2
Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifying effective strategies through…
Dual-Pool Token-Budget Routing for Cost-Efficient and Reliable LLM Serving
Xunzhuo Liu, Bowei He, Xue Liu +3
Production vLLM fleets typically provision each instance for the worst-case context length, leading to substantial KV-cache over-allocation and under-utilized concurrency. In pract…
Knowledge Access Beats Model Size: Memory Augmented Routing for Persistent AI Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Production AI agents frequently receive user-specific queries that are highly repetitive, with up to 47\% being semantically similar to prior interactions, yet each query is typica…
Visual Confused Deputy: Exploiting and Defending Perception Failures in Computer-Using Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Computer-using agents (CUAs) act directly on graphical user interfaces, yet their perception of the screen is often unreliable. Existing work largely treats these failures as perfo…
Adaptive Vision-Language Model Routing for Computer Use Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Computer Use Agents (CUAs) translate natural-language instructions into Graphical User Interface (GUI) actions such as clicks, keystrokes, and scrolls by relying on a Vision-Langua…
98 Faster LLM Routing Without a Dedicated GPU: Flash Attention, Prompt Compression, and Near-Streaming for the vLLM Semantic Router
Xunzhuo Liu, Bowei He, Xue Liu +3
System-level routers that intercept LLM requests for safety classification, domain routing, and PII detection must be both fast and operationally lightweight: they should add minim…
STELP: Secure Transpilation and Execution of LLM-Generated Programs
Swapnil Shinde, Sahil Wadhwa, Andy Luo +2
Rapid evolution of Large Language Models (LLMs) has achieved major advances in reasoning, planning, and function-calling capabilities. Multi-agentic collaborative frameworks using…
Beyond Fixed Rounds: Data-Free Early Stopping for Practical Federated Learning
Youngjoon Lee, Hyukjoon Lee, Seungrok Jung +4
Federated Learning (FL) facilitates decentralized collaborative learning without transmitting raw data. However, reliance on fixed global rounds or validation data for hyperparamet…
Building Safe GenAI Applications: An End-to-End Overview of Red Teaming for Large Language Models
Alberto Purpura, Sahil Wadhwa, Jesse Zymet +5
The rapid growth of Large Language Models (LLMs) presents significant privacy, security, and ethical concerns. While much research has proposed methods for defending LLM systems ag…
Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment
Melissa Kazemi Rad, Huy Nghiem, Andy Luo +3
Large Language Models (LLMs) have demonstrated powerful capabilities that render them valuable in different applications, including conversational AI products. It is paramount to e…