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The Signal

Everything that matters in AI, with our take.

Updated through the day. Every headline links straight to the source. The two lines underneath are ours.

arXiv cs.CLPaper

Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

This benchmark exposes a real gap: models look good on short-horizon reasoning but fail on the long, rule-heavy tasks that matter in regulated industries. If you're deploying LLMs in healthcare or legal, this is the kind of reasoning your system must handle. The benchmark itself becomes a bar for model selection and an early warning system for when models will fail in production.

arXiv cs.LGPaper

DRACO: Fine-Grained Credit Assignment with Dynamic Rubrics for Long-Horizon Agent Training

This tackles a real problem: rubric-based rewards are coarse, but you need fine-grained signal for step-level learning. The closed-form redistribution is elegant and the results on AppWorld suggest it matters. If you're training agents with outcome-blind rewards, this is worth implementing, though the benchmark is still narrow.