paper-with-me

Papers

Rediscovery

2025-04-28 · Martino Banchio, Suraj Malladi

We model search in settings where decision makers know what can be found but not where to find it. A searcher faces a set of choices arranged by an observable attribute. Each period, she either selects a choice and pays a cost to learn about its quality, or she concludes search to take her best discovery to date. She knows that similar choices have similar qualities and uses this to guide her search. We identify robustly optimal search policies with a simple structure. Search is directional, recall is never invoked, there is a threshold stopping rule, and the policy at each history depends only on a simple index.

📄 PDF Abstract BibTeX arXiv:2504.19761

Code (0)

등록된 구현이 없습니다.

Tasks

Attribute

Methods 이 논문이 사용한 방법론

SET Dynamic Sparse Training method where weight mask is updated randomly periodically

Similar Papers 제목 키워드 기반

The Rediscovery Hypothesis: Language Models Need to Meet Linguistics

2021-03-02 · Vassilina Nikoulina, Maxat Tezekbayev, Nuradil Kozhakhmet, Madina Babazhanova 외

There is an ongoing debate in the NLP community whether modern language models contain linguistic knowledge, recovered through so-called probes. In this paper, we study whether linguistic knowledge is a necessary conditi…

Language ModelingLanguage Modelling

FIRE-Bench: Evaluating Agents on the Rediscovery of Scientific Insights

2026-02-02 · Zhen Wang, Fan Bai, Zhongyan Luo, Jinyan Su 외 arxiv

Autonomous agents powered by large language models (LLMs) promise to accelerate scientific discovery end-to-end, but rigorously evaluating their capacity for verifiable discovery remains a central challenge. Existing ben…

Fast Symbolic Regression Benchmarking

2025-08-20 · Viktor Martinek arxiv

Symbolic regression (SR) uncovers mathematical models from data. Several benchmarks have been proposed to compare the performance of SR algorithms. However, existing ground-truth rediscovery benchmarks overemphasize the …

Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks

2026-06-01 · Dipesh KC, Anjila Budathoki arxiv

Coding-agent benchmarks evaluate whether a single uninterrupted agent can resolve a repository issue. Real software work is messier: tasks are interrupted, reassigned, reviewed, and resumed from partial states left by an…

Benchmarking Mythos-Linked Bug Rediscovery

2026-05-17 · Isaac David, Arthur Gervais arxiv

Anthropic's April 2026 Mythos materials combine benchmark claims with concrete bug-finding stories across OpenBSD, FreeBSD, Linux, FFmpeg, and browsers. This paper reports a controlled target-file rediscovery experiment …