Incomplete In-context Learning (2026 · 2 citations)
Standard in-context learning assumes that the retrieval pool has demonstrations for every output label. This paper drops that assumption. It studies cases where some classes have no labeled examples, for instance because the database is outdated, classes are highly imbalanced, or annotation follows a…
Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications (2026)
Current LLM safety evaluation depends on two approaches. Static benchmarks are costly, prone to contamination, and age quickly. Red-teaming is heuristic, and neither can show which policy clauses were actually tested. The authors propose POLARIS, which borrows specification-based testing from software engineering. It…
Task-Related In-Context Learning (2026)
Conventional in-context learning (ICL) presumes that the retrieval pool and the test set use the same label inventory.

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Papers of our library cite their works 2 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated 1 November 2026