arXiv AI By Stephen Mell, Botong Zhang, David Mell, Shuo Li, Ramya Ramalingam, Nathan Yu, Stephan Zdancewic, Osbert Bastani

Quasar: A Programming Language Specialized for LLM Code Actions

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Quasar is a new programming language designed to improve large language model (LLM) code actions by separating internal program logic from external tool calls. It allows developers to annotate external calls with effect information and modify internal execution to track these effects, enabling easier implementation of new features. The authors demonstrate Quasar’s utility by adding access control, autoparallelization, and conformal prediction for uncertainty quantification.

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arXiv AI
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Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark

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arXiv:2601. 01569v4 Announce Type: replace Abstract: LLM-based agents are increasingly capable of complex task execution, yet current agentic systems remain constrained by text-centric paradigms that struggle with long-horizon tasks due to fragile multi-turn dependencies and context drift.

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