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artificial intelligence

14,515 papers

#artificial intelligence Review Oct 2026

Joint Workflow and Prompt Optimization for User Behavior Simulation

User behavior simulation is the computational modeling of user interactions within information systems through the use of simulated agents in place of live users. It supports system testing and evaluation, decision-making and forecasting, and user experience design. Existing simulators rely on hand-crafted rules or dom...

Ni-Er Wu, Hong-Zhi Yin, Hui Li et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Towards the Automatic Synthesis of Interpretable Chess Tactics

State-of-the-art reinforcement learning agents are capable of outperforming human experts at games like chess, Go and StarCraft II. These agents do not simply take advantage of their digital hardware in being able to react and calculate faster than humans, but employ better strategies that lead to more victories. Inter...

Abhijeet Krishnan, C. Martens · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Learning Explainable Representations of Complex Game-playing Strategies

As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules to improve their performance. These concepts are applied to explain other players' actions, and to inform their own actions in-game. Understanding other players' strat...

Abhijeet Krishnan, Colin M. Potts, Arnav Jhala et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Explore, Then Commit: Measurement-Efficient Scientific Law Discovery with Language Models

Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol in which a large language model proposes hypotheses, a programmatic planner gathers measurements, and a fresh prompt synthesizes the final law from fixed observations....

Kautik Mandve, Dileepa Fernando · 0 citations
#artificial intelligence Preprint Oct 2026

Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution

Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets. Protein language models (PLMs) provide rich representations for this task, but task-agnostic zero-shot scores can be misaligned with a target assay, while supervised search in high-dimensional embedding spaces...

Si-Yuan Ma, Can-Ran Xiao, Zi-Kai Xiao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Modeling Latent Disturbances for Robust Decision-Making in World Models

In this paper, we study robust decision-making in the latent space of world models (WMs). Robust optimization is a mathematical framework where, given explicitly specified dynamics and physically meaningful disturbances, a robot can select actions that remain effective even under worst-case disturbances. However, apply...

Junwon Seo, Andrea Bajcsy · 0 citations
#artificial intelligence Preprint Oct 2026

Recurrent Looped Transformer

State tracking requires an update at every input, but the depth a Transformer applies to each token is fixed regardless of sequence length. We introduce the Recurrent Looped Transformer (RLT), which splits its layers between a parallel causal encoder and a recurrent decoder. At each token, the decoder merges the encode...

Yi-Fan Zhang, Ji-Chen Feng, Shi-Han Qin · 0 citations
#artificial intelligence Preprint Oct 2026

Personal-Agent Mediated Recommendation with Cross-Platform User History

Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the user's behalf across services. We formalize this emerging paradigm as Personal-Agent Mediated Recommendation: a platform recommender ranks a candidate set using platfor...

Yu Xia, Jiang-Fan Zhang, Jun Xiao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Seeing the Invisible: Physics-Guided Visual Prompting for Temperature- and Radiation-Aware VLA Navigation

Vision-Language-Action (VLA) models have become a major paradigm for Vision-and-Language Navigation (VLN). However, in safety-critical facilities, invisible risks such as radiation or temperature spikes cannot be detected by an RGB camera, and handling each risk is expensive, requiring a new encoder, new data, and mode...

Hojoon Son, Fan Zhang · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Does Muon Need Fine-Grained Spectral Shaping?

Muon combines current and past gradients into matrix momentum. For $M=U\Sigma V^\top$, the idealized polar update $Q=UV^\top$ gives every singular direction the same weight. We refer to this as the flat profile. Several recent optimizers replace this flat profile with fine-grained spectral maps that give each direction...

Meher Chaitanya, Tianyi Zhou, Aristides Gionis · 0 citations
#artificial intelligence Preprint Oct 2026

DeepAJM: Deep Association Joint Model for Irregularly Sampled data

Joint Models simultaneously model longitudinal and survival outcomes, leveraging patterns in patients'longitudinal trajectory to improve the prediction of survival outcomes. The classical parametric joint models, however, rely on fixed parametric assumptions, making them susceptible to bias under model misspecification...

Barsha Halder, Jeffrey A. Thompson · 0 citations
#artificial intelligence Preprint Oct 2026

Logbook: Extremely Long-form Audio Event Understanding

Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we introduce Logbook, a benchmark for hour-scale audio understanding, with recordings ranging from ten minutes to six days. Given a continuous audio recording and an event label...

Kwanghee Choi, Suwon Shon, Dmitriy Serdyuk et al. · 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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