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artificial intelligence

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#artificial intelligence Preprint Oct 2026

Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons

HRF-Res, a liquid state machine in which LIF neurons are replaced by a heterogeneous population of Harmonic Resonate-and-Fire neurons, achieves state-of-the-art accuracy among spiking reservoir methods and demonstrates that introducing frequency-selective dynamics into spiking reservoirs improves representational quali...

Aurora Micheli, C. Gallicchio, Nergis Tömen · 0 citations
#artificial intelligence Review Oct 2026

FilingLoop: Evaluating and Evolving LLM Agents for Corporate Disclosure Review and Revision

FilingLoop connects the concerns an agent discovers with the company facts it obtains and the revisions it commits, providing requirement-level feedback for procedures used in later review tasks, and couples iterative review and revision within each case with procedural learning across cases.

Wen-Tao Zhang, Yi-Lei Zhao, Guang-Yan Gan et al. · 0 citations
#artificial intelligence Preprint Oct 2026

The Anatomy of Socio-Demographics in Pluralistic Offensiveness Modeling: When and Where It Helps, and the Role of Reasoning

The results suggest that the mixed evidence in prior work may partly stem from individual-level evaluation, and that the value of socio-demographic information depends on both how it is evaluated and how models are guided to use it.

Yifan Wang, Leixin Zhang, Jin-Yi Mu et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Verification Learning Theory: A Process Model of Checking and Retention in AI-Assisted Judgment

Verification Learning Theory formalises this possibility for claim-evaluation practice followed by correct, independent, rule-specific feedback and links perceived assistant reliability to evidence checking and links the history of those checks to retained rule use.

Christoph Trattner · 0 citations
#artificial intelligence Preprint Oct 2026

What Constitutes Food Similarity? Visual Representations and Retrieval in Indian Cuisine

The findings show that recognition performance alone cannot characterize relational structure: food similarity depends on representation, modality, and abstraction level rather than being a fixed property of the food collection.

Saransh Kumar Gupta, Akshadha Sharma, Lipika Dey et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Seq@K: Evaluating Language Models Under Sequential Feedback

This work introduces Seq@K, a natural evaluation protocol that measures whether a model can solve a problem within K sequential attempts, provided feedback after each previous failure, and establishes how Seq@K offers a more faithful metric for intelligent systems that typically operate in such feedback loop, and the n...

Thomson Yen, Gilbert Yang, Nai-Meng Ye et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Evaluating and improving AI agents for sequencing protocol understanding

LibStructBench is introduced, a document-grounded benchmark for reconstructing sequencing-library structures and molecular workflows and shows that frontier agents often produce approximately correct reconstructions but remain unreliable at exact reconstruction, particularly in molecular-state representation and workfl...

Chi-Lam Poon, Michael Goneos, Zezheng Song et al. · 0 citations
#artificial intelligence Preprint Oct 2026

What Does an Ontology Catch? Curated, LLM-Generated and Data-Derived Ontologies as Checkers of LLM Agents over Knowledge Graphs

This work accounts for what ontology-derived checks catch and what they wrongly flag, and shows how each source trades caught errors against false alarms, how a curated schema used as published can contradict its own data, which errors structural checks miss, and whether combining sources or giving the agent the checke...

Michał Orzechowski, Rund Tawfiq, T. Kościółek · 0 citations
#artificial intelligence Preprint Oct 2026

WebAnything: From the Wild Web to Scalable Agent Environments

This work presents WebAnything, a fully automated framework that reconstructs source-grounded, reusable Web environments from real URLs without per-site manual implementation or repair after initial setup and authorization.

Tian-Ci Xie, Zi-Kun Cai, Chao-Yun Zhang et al. · 0 citations

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