AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Coding agents produce large, tangled patches that mix multiple development purposes, making the code hard to review and maintain. Commit untangling offers the promise of organizing such large patches into untangled, manageable commits. This paper emphasizes two important limitations in existing commit untangling studie...
SemanticSpec introduces a semantic probability estimation mechanism that probes the model's internal hidden states to assess the likelihood of generating sequences with specific meanings, and proposes SemanticSpec, a semantic-aware speculative decoding framework that verifies entire semantic sequences instead of tokens...
This work proposes LLMSafeGuard, a lightweight real-time framework that integrates an external validator into decoding, rejecting unsafe outputs while allowing valid ones, and introduces a similarity-based validation approach, simplifying safety constraint validation and eliminating the need for external control model...
Coding agent infrastructure is shifting from harness engineering toward loop engineering as coding agents are deployed for sustained long-horizon software development. Existing benchmarks often center on localized tasks or end-state outcomes, offering limited insight into sustained execution. We introduce LOOPSBENCH, a...
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