Skip to content

Category

artificial intelligence

14,558 papers

#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
#artificial intelligence Preprint Open access Oct 2026

Lineage-Aware Memory Governance: A Derivation-Gated Framework for Privacy-Preserving Column-Level Access Control in Enterprise AI Agents

Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results the requester could not derive, and departments can silently compute a same-named key performance indicator (KPI) through conflicting logic. Existing agent-memory systems (e.g., MemGP...

Venkata M Sangaraju, Sudhir Vissa · 0 citations
#artificial intelligence Preprint Oct 2026

CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets

Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful reading of accompanying dataset documentation. We present the first benchmark enabling end-to-end evaluation of metadata extraction aligned with a community-standard schema....

Berke Arda, Ahmetcan Yavuz, Paul Gerry et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Is this machine playing?

We placed a modern AI coding assistant in an unintended role: as the mind of a body on an unknown digital island. With only a minimal instruction mentioning no specific task, reward, or activity, the machine started animating its virtual body. Across thirty-hour runs, the embodied AI agent climbed hills, stacked blocks...

Nathan Cloos, Antonio Norelli, Daniel Durbin et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Jailbreaking Open-Weight LLMs via Random Embedding Perturbations

While open-weight models have enjoyed steady progress in capabilities and wide adoption across multiple domains, their safety remains an important concern. One key feature is the ability to refuse or deflect harmful, malicious, or insensitive prompts. In this paper, we expose safety vulnerabilities across six common op...

Abhinav Sudhakar Dubey (University of California Santa Cruz), Scott Sirri (University of California Santa Cruz), Vaggos Chatziafratis (University of California Santa Cruz) et al. · 0 citations
#artificial intelligence Preprint Oct 2026

AMBER: Training Long-Horizon Web Agents through Append-Only Memory

Modern language-model agents increasingly interact with external environments over long-horizon, multi-step trajectories, where the accumulated interaction history can quickly exceed practical context budgets. To ensure reliability, agents must maintain factual information over long horizons, remember execution errors...

Chinmay Savadikar, Zhao-Yu Zhang, Ming-Yu Zhao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Towards a Unified Misuse Monitoring Benchmark

LLM agents increasingly act in multi-actor environments, exposing them to misuse from multiple sources: decomposition attacks, where a harmful request is split into innocuous sub-requests, and prompt injection attacks, where a compromised tool delivers a malicious instruction. Existing evaluations treat these threats s...

Aniruddh Pramod, James Oldfield, Adel Bibi · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Inference-Time Projection for Physically Valid Biomolecular Diffusion Models

AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically invalid: chains overlap at interfaces, ligand bond lengths and angles are distorted, rings are non-planar, and stereocentres are inverted. Current approaches either steer...

Qurat-ul-ain, Yee Whye Teh, Charlotte M. Deane et al. · 0 citations

From tech blogs

See all →
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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.