AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 29 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
How many tokens from its context does a language model actually use, and what determines that number? We study this question through self-attention. Without retraining, we retain only the tokens with the highest attention weights at each head, layer, and query, keeping their original weights unchanged. By varying the s...
Transformer language models build predictions through successive residual updates, but how their representations become specific to an eventual outcome remains unclear. We study this process by comparing intermediate residual states with their own final states and an empirical bank of final states from other contexts....
Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often overlooking the challenges posed by human presence and high-level behavior. To address this vacancy, we present HINT-Plan, a novel approach to integrate human intention p...
Detecting whether a jailbreak attack against a large language model (LLM) has succeeded is a challenging problem in AI security. Existing approaches rely on brittle string matching, expensive LLM-based judges, or task-specific classifiers that often fail to generalize. This paper investigates whether semantic coherence...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.