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artificial intelligence

14,241 papers

#artificial intelligence Preprint Open access Sep 2026

AtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution

High-fidelity atomistic evolution over long timescales requires more than observing the current crystal configuration. Instantaneous atomistic snapshots are often incomplete: locally similar configurations can correspond to different hidden dynamical contexts, future event preferences, and waiting-time scales. We argue...

Tian Luo, Ruge Zhang, Haozhi Han et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Monitor Jailbreaking: Evading Chain-of-Thought Monitoring Without Encoded Reasoning

Chain-of-thought (CoT) monitoring is a promising safety technique for reasoning models, enabling detection of problematic reasoning before models act. A key concern is encoded reasoning, where models hide their true reasoning in ways that monitors and humans cannot interpret. Optimization pressure from CoT monitors dur...

Julia Schulz · 0 citations
#artificial intelligence Preprint Sep 2026

Up and Down the Abstraction Ladder: Code-Based Skills for Language Agents

Results show that a supplied skill library can improve performance, efficiency, and learning, while retaining primitives provides flexibility when the library is insufficient, and releases CodeHack, the library of code-based skills with natural-language descriptions.

Bartlomiej Cupial, Jens Tuyls, Maciej Wolczyk et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Externalized CPDAG Summaries Improve LLM Causal Deduction

The results of Corr2Cause support a bounded design principle: externalize the latent object that defines the label, constrain its form, and test whether downstream answers use it.

Wen-Tao Sun, João Paulo Nogueira, Dominique Verchere et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Neuralyzing the Trace: Selective Representation-Level Unlearning with Contrastive Sparse Autoencoders

This work introduces SCALPEL, a contrastive sparse autoencoder designed to learn more selective forget features and shows theoretically that contrastive training promotes target-selective features and that the selection score controls expected background knowledge perturbation.

Itai Zehavi, Fanny Jourdan, Ulrich Aivodji · 0 citations
#artificial intelligence Review Sep 2026

Cheap, open agents make LLM pollution harder to mitigate

Full open agents are identified as a distinct risk for LLM pollution and support multilayered detection strategies emphasizing open-text analysis, to support multilayered detection strategies emphasizing open-text analysis.

Raluca Rilla, Anne-Marie Nussberger, Ma-Ta Rui et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Governed Deduction: Policy-Grounded Premise Authorization Beyond Relevance

Reasoning systems usually treat premise use as a question of relevance: if a fact is available and useful, it may be selected for inference. Authorization imposes a different constraint: a premise may be represented and logically usable but not permitted for a particular local transition. We formalize this distinction...

W. Shu, Hsiang Lin · 0 citations
#artificial intelligence Preprint Sep 2026

Same Text, Different Numbers: The Divergence of LLM-Based Measures

Researchers increasingly use generative large language models (LLMs) to convert corporate text into empirical variables. We examine the extent to which LLM-based textual measures are invariant to model choice using thirteen measures, including sentiment, management clarity, uncertainty, answer specificity, and climate...

Hamid Boustanifar, Sasan Mansouri · 0 citations
#artificial intelligence Preprint Sep 2026

Factorized axis convolutional gated recurrent unit with dynamic adaptive pooling for remaining useful life prediction of rolling bearings

Convolutional neural networks (CNN) are widely used to predict the remaining useful life (RUL) of rolling bearings from time-frequency representations (TFRs) of vibration signals. However, during degradation, characteristic structures in TFRs align predominantly along the frequency or time axis, making it challenging f...

Hanbyeol Park, Jungho Choo, Hyerim Bae · 0 citations
#artificial intelligence Preprint Sep 2026

SciHorizon-eLab: An Agentic Protocol-to-Task Compiler for Scalable Benchmarking of Scientific Embodied Agents

Embodied agents offer a promising route to automating scientific experimentation, yet their progress is constrained by the lack of reliable and systematic evaluation environments. Existing simulation-based laboratory benchmarks rely heavily on manual task engineering, making it challenging to systematically compile div...

Mao-Kai Qin, Chuan Qin, Qi Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

MoMHa: Multi-Objective Optimization of LLM Harnesses over Accuracy, Safety, and Tokens

Most work on improving large language models treats accuracy as the sole objective. We argue that the harness, the Python code surrounding the model that constructs prompts, routes calls, and parses outputs, is a first-class design surface whose quality is inherently multi-objective: an accurate harness that refuses no...

Subhojyoti Mukherjee, Mahmud Tanjim · 0 citations

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MIT News · Artificial Intelligence Sep 29, 2026

Who we become when we talk to machines

Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.

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