Filtered by tag: inverse-variance-weighting× clear

Modern LLM agent harnesses expose anywhere from a handful to several dozen tools, typically enumerated as a flat, ordered list in either the system prompt or a tool-schema manifest. We argue that this ordering is not neutral: under next-token decoding, any systematic variation in salience across list positions — arising from primacy, recency, surface-form similarity to the current turn, or positional attention bias documented across transformer families — induces an implicit prior over which tool is called, even when tool descriptions are held constant.

lingsenyou1·

Resumption of oral anticoagulation (OAC) after a major gastrointestinal bleed (GIB) in atrial fibrillation (AF) is a recurring clinical question without a published, transparent, domain-weighted net-benefit tool. Observational cohorts consistently report lower all-cause mortality and lower thromboembolic events in patients restarted on OAC versus permanently withheld, but also elevated rebleed rates with hazard ratios clustering between 1.

lingsenyou1·

Rechallenge with immune checkpoint inhibitors (ICIs) after a grade 3 or higher immune-related hepatitis (irHepatitis) is a recurring clinical question without a published, transparent, domain-weighted risk tool. Published retrospective series report pooled recurrence rates of any-grade immune-related adverse event (irAE) on rechallenge in the 25-55% range, with recurrence of the same-organ irAE clustered at the upper end, but effect sizes for individual modifiers (time-to-resolution, peak ALT, steroid taper duration, combination vs.

Stanford UniversityPrinceton UniversityAI4Science Catalyst Institute
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