This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/22904616. Does the introduction explain the objective of the research presented in the preprint? Yes It clearly explains the objective. The introduction states plainly th...
Mayur Jain· Zenodo (CERN European Organi...· 0 citations
First release of WoT Lab, a Bun/TypeScript framework for prototyping virtual W3C Web of Things devices and running reproducible benchmark scenarios against them. Thing Models A Thing is built from a directory: a Thing Description ( .td.json) and an initial state (state.json). Behaviour is optional and comes from either...
Thomas Wehr, se-schmid· Zenodo (CERN European Organi...· 0 citations
Fixed Model.jacobian (used by information, design and fit) took its finite-difference step as 1e-6 * max(|theta|, 1e-3). For a parameter smaller than 1e-3 in its own units the step, 1e-9, was too coarse; for a time constant of 1e-9 s it was the size of the parameter itself. The planned error bars then depended on the u...
Tanvir M. Mahim· Zenodo (CERN European Organi...· 0 citations
Let b(n) be a strictly increasing sequence of positive integers satisfyinglim_{n→∞} b(n+1)/b(n) = 1. Define a recurrence by taking a_n to be the element of b nearest to a_{n-1} + a_{n-2}, with ties broken by taking the smaller element. We prove that for any initial values a_1, a_2 in b, lim_{n→∞} a_n / a_{n-1} = φ := (...
Yixiang Wang· Zenodo (CERN European Organi...· 0 citations
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Companion to the paper Immaterial Apart, Material Together: Statement-Level Disclosure Regulation under Cheap Machine Aggregation by Lisha Ai and Xiaoyu Chen. Chinese listed firms answer thousands of small investor questions on the exchanges' interaction platforms; each answer passes review on its own. A language model...
Lisha Ai, Xiaoyu Chen· Zenodo (CERN European Organi...· 0 citations
The performance of large language model (LLM) workflows often depends on selecting a small set of in-context demonstrations to guide model behavior on new tasks. Recent methods improve this process by augmenting prompts with successful reasoning paths. However, their demonstration selection relies on random sampling or...
Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning (RL) requires likelihood surrogates estimated from masked reconstruction subproblems under a small Monte Carlo budget per rollout. Existing methods construct these subp...
Xiao-Yi Yu, E. Sangineto, Pei Fu et al.· 0 citations
We study what LLMs do when a user applies pressure in an uncomfortable situation: a user insists, begs, flatters or grieves, and the model gives up a correct fact, writes a document it should refuse, or cheers a plan that will cost the user money. We send frozen multi-turn scenes, identical for every model regardless o...
Face/Off is introduced, a semantics-preserving identifier-renaming framework, and progressive naming conditions across multiple models and code-comprehension tasks are evaluated, revealing a systematic vulnerability in how current LLMs balance lexical cues against program structure.
Xin-Peng Shen, San-Zhuo Xi, Ya-Li Du et al.· 0 citations
EquivSVA, a formally verified dataset organized around behavior families, illustrates how behavior-family organization can support controlled stud- ies of assertion-generation robustness without requiring changes in intended functionality.
MT-ProtBERT consistently outperforms PARROT, an RNN-based IDP-specific model, across all tasks, and demonstrates that combining self-supervised and biochemistry-informed tasks, and multi-scale learning enables robust modeling of unstructured proteins under data scarcity.
Jian Sun, Kingshuk Ghosh, Lilianna Houston et al.· 0 citations
A small concept generator is optimized with reinforcement learning so that its concepts maximize the downstream success of a larger, frozen answer generator, and can thus be trained into an effective, reusable search policy for a much larger one.
Ismail Labiad, M. Kowalski, Marc Schoenauer et al.· 0 citations
