Modern software relies heavily on third-party software libraries to streamline the development process. The act of switching one library for a similar counterpa...
Tool-using LLM agents face a reliability-cost tradeoff: routing every decision through the LLM improves correctness but incurs high latency and inference cost, ...
The carbon footprint of academic conferences becomes a topic of increasing debate. It is important to consider whether the benefits derived from attending confe...
Compliance as code is an emerging idea about automating compliance through programmed compliance controls and checks. Given scant existing research thus far, th...
Edge computing environments host increasingly complex microservice-based IoT applications that are prone to performance anomalies propagating across dependent s...
This is the first of five papers comprising The Semantic Arrow of Time. The argument begins with a claim: computing's arrow of time is semantic, not thermodynam...
Message passing is widely assumed to be a fundamental primitive of distributed systems. This paper argues that conventional message systems embed a category mis...
Speculative Decoding (SD) has emerged as a premier technique for accelerating Large Language Model (LLM) inference by decoupling token generation into rapid dra...
Determining a winner among a set of items using active pairwise comparisons under a limited budget is a challenging problem in preference-based learning. The go...
We develop a discrete gauge-theoretic framework for superposition in large language models (LLMs) that replaces the single-global-dictionary premise with a shea...
This paper presents a controlled empirical study of biologically motivated local learning for handwritten digit recognition. We evaluate an STDP-inspired compet...
Dense 4D reconstruction from unposed images remains a critical challenge, with current methods relying on slow test-time optimization or fragmented, task-specif...
