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artificial intelligence

20,515 papers

#artificial intelligence Preprint Open access Oct 2026

3DCodeVerse: Exploring 3D Worlds as Code

We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises large-scale, high-quality datasets of executable 3D code, a coding harness for spatial reasoning and automated verification, and practical guidance for 3D coding. First,...

Yipeng Gao, Ziyao Zeng, Jinfa Huang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Dexterity from Supervised Play

How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present DSP: Dexterity from supervised play, a framework in which a robot learns a play policy from minutes of human play through behavior cloning, then deploys it autonomously to collect hours of interaction data...

Botao He, Yiming Dou, Yiannis Aloimonos et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

ACEdit: Stable Multi-Turn Image Editing via Asymmetric Conditioning

Image editing models produce impressive results for individual edits, but their quality often deteriorates over multiple editing turns. Each editing turn introduces small distribution shifts that accumulate over successive edits, creating a gap between the input distributions encountered during the editor's original tr...

Sara Dorfman, Nir Goren, Gal Barak et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Learning Self-Orchestration in Decentralized Agent Swarms

The capabilities of an agent swarm depend on both its individual members and how they coordinate. Yet existing multi-agent systems often train agents within fixed orchestration structures, separating the learning of individual capabilities from the organization of collective behavior. We introduce market-based post-tra...

Guowei Xu, Zhenting Qi, Amani Kiruga et al. · 0 citations
#artificial intelligence Preprint Oct 2026

AVC-Reward: Event-Centric Audio-Video Consistency Evaluation

An event-centric evaluation framework that disentangles audio and visual events at the event level, analyzes each event independently, cross-validates relations across modalities, and aggregates the judgments into a coarse-to-fine, three-level consistency metric, providing a general formulation for audio-video consiste...

Yu-Ruo Wu, Kai-Hang Pan, Kai Shen et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Learning to Steer LLM Agents and Multi-Agent Systems

This work proposes a steering agent that supervises execution on the fly and steers the system back on track when drift occurs, and jointly train the two paths with reinforcement learning, combining a pairwise ranking objective with group-relative policy optimization (GRPO).

Le-Yang Shen, Ya-Xin Gong, Yang Zhang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Knowledge That Is Linear Before Fine-Tuning Generalizes After It

Not all facts a language model can recall support further learning equally well. We distinguish active facts, which support generalization beyond their own recall, from inert facts, which can be recalled but do not support such generalization in a given task. We study this distinction by constructing new relations from...

Faridoun Mehri, Hinrich Sch\"utze · 0 citations
#artificial intelligence Review Oct 2026

AI Consilium: a Benchmark of LLM Clinical Multidisciplinary Second Opinions

Large language models (LLMs) can generate differential diagnoses for complex cases, but a useful second opinion must also be factually grounded, clinically coherent, actionable, and safe. We developed a multidimensional benchmark using 300 diagnostically resolved NEJM--MedQA cases: 110 for physician reference ratings a...

А. А. Боков, I. Panin, N. Nechaev et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Towards Continual Learning: Mitigating Forgetting With Subspace Tuning

Large language models (LLMs) acquire new skills through fine-tuning, but it can destroy capabilities they already have: catastrophic forgetting remains a central obstacle to continual learning in LLMs. Recent works connect forgetting to how far, and along which directions, fine-tuning moves the weights. On-policy metho...

Arnav Chavan, Kusha Sareen, Rishabh Tiwari et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Librarian Agents: Training LLMs to Curate Long-Context Workspaces that Anticipate Future Queries

Reasoning over long document contexts remains a challenge for large language models (LLMs). Standard retrieval methods are inherently reactive, bottlenecking agents with complex, cross-document reasoning at inference time, while precomputed structures like knowledge graphs often fall short because they rely on rigid he...

Anikait Singh, Teresa Zhang, Yoonho Lee et al. · 0 citations

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Hugging Face Blog Nov 10, 2026

Decision Models in Hugging Face

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