Search: “models”

Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation

arXiv:2411.15490v2 Announce Type: replace Abstract: Acute ischemic stroke (AIS) requires time-critical decision-making, where inaccurate interpretation of neuroimaging findings can lead to irreversibl

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Research

In-context Region-based Drag: Drag Any Region to Any Shape

DGX agent

arXiv:2606.25907v1 Announce Type: new Abstract: Diffusion models have shown promise in drag-style editing. Previous works mainly focus on point-based drag, which is inherently ambiguous. This paper fo

researcharxiv-cs-cv

25 Jun 2026

Laplace--Fisher Gate Identities for Optimal Matrix-Gated Blended Score Estimation

arXiv:2606.25169v1 Announce Type: cross Abstract: Sampling from an unnormalized target by reversing an Ornstein--Uhlenbeck diffusion requires the score of each noise-perturbed marginal. Tweedie's iden

MINIF2F-DAFNY: LLM-Guided Mathematical Theorem Proving via Auto-Active Verification

arXiv:2512.10187v3 Announce Type: replace Abstract: LLMs excel at reasoning, but validating their steps remains challenging. Formal verification offers a solution through mechanically checkable proofs

Multi-Agent Goal Recognition with Team- and Goal-Conditioned Reinforcement Learning and Factorized Branch-and-Bound

arXiv:2606.25978v1 Announce Type: cross Abstract: Multi-agent goal recognition asks an observer to jointly infer which agents act together and what each team is trying to achieve, so the hypothesis sp

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients

arXiv:2606.25008v1 Announce Type: cross Abstract: Neural scaling laws describe how pre-training loss decays as power laws with training time, model size, and compute. This position paper argues that t

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On-Policy Self-Distillation with Sampled Demonstrations Reduces Output Diversity

arXiv:2606.26091v1 Announce Type: new Abstract: On-policy self-distillation achieves strong pass@1 accuracy by using a single model as both teacher and student, with the teacher conditioned on a corre

safetyarxiv-cs-lg

Optimizing Abstractive Summarization With Fine-Tuned PEGASUS

arXiv:2606.25462v1 Announce Type: new Abstract: Abstractive text summarization is the technique of generating a short and concise summary comprising the salient ideas of a source text without making a

Our new AI policy is that the White House decides ad hoc, for whatever reasons it likes, who does and does not get access to frontier intell…

model-releasesgary-marcus--x

Our new AI policy is that the White House decides ad hoc, for whatever reasons it likes, who does and does not get access to frontier intelligence. This seems rather maximally terrible. The US Governm

S^{2}-FracMix: Label-Preserving Self-Saliency Mixup Augmentation

arXiv:2606.25784v1 Announce Type: new Abstract: Data augmentation is known to improve generalization of deep visual models. Recent methods favor mixup strategies that generate interpolated samples to

researcharxiv-cs-cv

Sampling Strategies for Robust Universal Quadrupedal Locomotion Policies

model-releasesarxiv-cs-ro

arXiv:2510.07094v2 Announce Type: replace Abstract: This work focuses on sampling strategies of configuration variations for generating robust universal locomotion policies for quadrupedal robots. We

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems

arXiv:2606.25533v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retri

local-aiarxiv-cs-cl

Agents

Skill-MAS: Evolving Meta-Skill for Automatic Multi-Agent Systems

arXiv:2606.18837v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based automatic Multi-Agent Systems (MAS) generation has become a crucial frontier for tackling complex tasks. Howe

agentsarxiv-cs-lg

Spatio-Temporal Retrieval-based Priors for Adaptive Computational Teaching in Driving

arXiv:2606.25224v1 Announce Type: new Abstract: Learning-based automated coaching systems for complex motor tasks such as high-performance driving remain limited in the ability to be adaptive by their

local-aiarxiv-cs-ro

Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing

model-releasesarxiv-cs-ro

arXiv:2606.25754v1 Announce Type: new Abstract: Polishing is a critical finishing process in high-end manufacturing fields such as aerospace, where surface quality directly affects the service perform

TACO: Towards Task-Consistent Open-Vocabulary Adaptation in Video Recognition

arXiv:2606.25478v1 Announce Type: new Abstract: Adapting CLIP for open-vocabulary video recognition necessitates a delicate balance between newly acquired video knowledge and the pretrained generaliza

Tensorion: A Tensor-Aware Generalization of the Muon Optimizer

arXiv:2606.25975v1 Announce Type: cross Abstract: Common first-order optimizers, such as Adam, implicitly treat each parameter block as an unstructured vector, which disregards the multilinear weight

Toten: A Knowledge-Based System For Structure-Preserving Representation Of Physical Quantities And Technical Notation In Brazilian Portuguese

model-releasesarxiv-cs-cl

arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expression

Applications

Towards Continuous Power Forecasting: Practical Continual Learning for Real-World Energy Systems in Nonstationary Time Series

arXiv:2606.24955v1 Announce Type: new Abstract: Power forecasting models deployed in real-world energy markets must operate under nonstationary conditions, where data distributions continually evolve

applicationsarxiv-cs-lg

Two-dimensional Hyperbolic RNN Neural Quantum State

arXiv:2606.25600v1 Announce Type: cross Abstract: In the first part of this work, we construct the first type of two-dimensional (2D) hyperbolic neural quantum state (NQS) in the form of the Lorentz 2

Two Stages of Folding: Convergent Mechanisms in AI Protein Folding Trunks

arXiv:2602.06020v3 Announce Type: replace Abstract: How do protein structure prediction models fold proteins? We investigate this question through causal interventions on the folding trunks of ESMFold

researcharxiv-cs-lg

USS: Unified Spatial-Semantic Prompts for Embodied Visual Tracking with Latent Dynamics Learning

arXiv:2606.25880v1 Announce Type: new Abstract: Embodied Visual Tracking (EVT) requires an agent to continuously follow a specified target while actively moving through dynamic environments. However,

Weave of Formal Thought

arXiv:2606.25987v1 Announce Type: new Abstract: Large language models (LLMs) attain remarkable surface fluency on code, yet they neither formally guarantee the syntactic validity of their output nor l

What Do Language Priors Contribute to Darcy-Flow Inversion? A Mechanistic Audit

arXiv:2606.24967v1 Announce Type: new Abstract: In ill-posed inverse problems, the recovered solution depends as much on the prior as on the data, yet much of the engineering knowledge that could serv

Safety

Why Multi-Step Tool-Use Reinforcement Learning Collapses and How Supervisory Signals Fix It

arXiv:2606.26027v1 Announce Type: new Abstract: Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancin

safetyarxiv-cs-cl

A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion

arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools fro

A Paninian Foundation for Indic Language Processing

arXiv:2606.24172v1 Announce Type: cross Abstract: More than a billion people communicate in Indic languages, yet the natural language processing infrastructure serving them remains fragmented and unde

A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching

arXiv:2606.24140v1 Announce Type: new Abstract: Discrete flow matching (DFM) provides a principled framework for generative modeling on discrete state spaces via continuous-time Markov chain dynamics.

local-aiarxiv-cs-lg

Acquisition state behaves as a structured, measurable variable governing lung-nodule AI: kernel-driven measurement instability and noise-driven detection fragility, invisible to DICOM metadata

arXiv:2606.12824v2 Announce Type: replace-cross Abstract: AI governance for medical imaging is formalizing: the 2026 ACR-SIIM Practice Parameter recommends local acceptance testing and ongoing drift m

Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods

arXiv:2606.24484v1 Announce Type: new Abstract: WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially mo

researcharxiv-cs-cv

AVOC: Enhancing Hour-Level Audio-Video Understanding in Omni-Modal LLMs via Retrieval-Inspired Token Compression

arXiv:2606.24286v1 Announce Type: new Abstract: Multimodal Large Language Models have achieved remarkable progress in short-form audio-video understanding, yet long-form audio-video comprehension rema

Safety

Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators

arXiv:2509.03647v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly serve as automated evaluators, yet they suffer from 'self-preference bias': a tendency to favor thei

safetyarxiv-cs-ai

Compact Object-Level Representations with Open-Vocabulary Understanding for Indoor Visual Relocalization

arXiv:2606.24767v1 Announce Type: new Abstract: Indoor visual relocalization plays a critical role in emerging spatial and embodied AI applications. However, prior research was predominantly devoted t

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages

arXiv:2606.23725v1 Announce Type: cross Abstract: Machine-learning screens for battery materials are trained and judged almost entirely against computed reference voltages, and those references carry

CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark

arXiv:2409.11363v2 Announce Type: replace-cross Abstract: AI agents have the potential to aid users on a variety of consequential tasks, including conducting scientific research. To spur the developme

Counting Trees from Satellite Imagery with Noisy Supervision

arXiv:2606.24786v1 Announce Type: new Abstract: Counting individual trees is a fundamental task for environmental monitoring, yet remains largely unexplored with satellite imagery. At these resolution

Tutorials

Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation

arXiv:2606.18478v2 Announce Type: replace Abstract: Recent progress has shown promise in distilling multi-step video diffusion models into efficient few-step students. Among them, Distribution Matchin

tutorialsarxiv-cs-cv

Decisions about how to use AI in your organization are increasingly organizational design and strategy decisions, not IT choices: How do you…

model-releasesethan-mollick--x

Decisions about how to use AI in your organization are increasingly organizational design and strategy decisions, not IT choices: How do you integrate agents into your firm? What intelligence will you

Differential Unfolding: Efficient Unfolding Reconstruction for Video Snapshot Compressive Imaging

arXiv:2606.24153v1 Announce Type: new Abstract: While Deep Unfolding Networks (DUNs) dominate video Snapshot Compressive Imaging (SCI), they remain constrained by a uniform design philosophy. Existing

Dimensionality Reduction of QAOA Parameter Space with Kernel PCA for Max-Cut

arXiv:2606.23718v1 Announce Type: cross Abstract: The Quantum Approximate Optimization Algorithm (QAOA) is a leading variational algorithm for combinatorial optimization on near term quantum devices.

Dirac-Frenkel dynamics with inertia for nonlinearly parametrized solutions of evolution problems

arXiv:2606.24769v1 Announce Type: cross Abstract: Even when Dirac-Frenkel dynamics determine a well-defined evolution in function space, the corresponding parameter dynamics can be non-unique or ill-c

DLTPose: 6DoF Pose Estimation From Accurate Dense Surface Point Estimates

arXiv:2504.07335v3 Announce Type: replace Abstract: We propose DLTPose, a novel method for 6DoF object pose estimation from RGBD images that combines the accuracy of sparse keypoint methods with the r

EchoFoley: Event-Centric Hierarchical Control for Video Grounded Creative Sound Generation

arXiv:2512.24731v2 Announce Type: replace Abstract: Sound effects build an essential layer of multimodal storytelling, shaping the emotional atmosphere and the narrative semantics of videos. Despite r

EComAgentBench: Benchmarking Shopping Agents on Long-Horizon Tasks with Distributed Hidden Intent

arXiv:2606.17698v2 Announce Type: replace Abstract: As LLM-based shopping agents enter production, existing benchmarks fail to capture how a shopper's requirements arrive: stated implicitly in the que

Faithful by Construction: Claim-Anchored Attribution for Multi-Document Summarization

arXiv:2606.23989v1 Announce Type: cross Abstract: End-to-end large language models (LLMs) produce fluent multi-document summaries but remain prone to hallucination, and the attributions they offer are

local-aiarxiv-cs-ai

FlowerDance: MeanFlow for Efficient and Refined 3D Dance Generation

arXiv:2511.21029v3 Announce Type: replace Abstract: Music-to-dance generation aims to translate auditory signals into expressive human motion, with broad applications in virtual reality, choreography,

GUI vs. CLI: Execution Bottlenecks in Screen-Only and Skill-Mediated Computer-Use Agents

arXiv:2606.24551v1 Announce Type: new Abstract: Computer-use agents can execute software tasks through either graphical interfaces or programmatic command interfaces, but existing evaluations confound

HelloTwin launches ‘Digital Authority’ to bring governed AI agents to the enterprise

model-releasessiliconangle

HelloTwin.ai GmbH today announced what it calls an accountable artificial intelligence AI twin that holds business intelligence and goals in a single source of truth. HelloTwin said it built its data