Search: “models”

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation

arXiv:2603.23867v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have been applied to a wide range of reasoning tasks, yet it remains unclear whether they can reason robustly un

researcharxiv-cs-ai

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ChronoFlow-Policy: Unifying Past-Current-Future Interaction Flow in Visuomotor Policy Learning

DGX agent

arXiv:2606.31493v1 Announce Type: new Abstract: Visual signals play a crucial role in policy learning by enabling models to capture object motion and interaction dynamics. Just as humans reason about

safetyarxiv-cs-ro

1 Jul 2026

CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning

arXiv:2606.31608v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong results on many medical benchmarks, but their clinical reasoning remains difficult to evaluate reliably. A c

safetyarxiv-cs-cl

Coarsening Bias from Variable Discretization in Causal Functionals

arXiv:2602.22083v2 Announce Type: replace-cross Abstract: Causal identification functionals often require integration over conditional densities of continuous variables, such as those arising in nonpa

CoMet: Context and Multiplicity Decomposition for Multimodal Uncertainty Estimation

arXiv:2606.32012v1 Announce Type: cross Abstract: Uncertainty estimation has been a long-standing challenge in AI models; it amounts to 'knowing what you don't know,' and metacognition is notoriously

researcharxiv-cs-cv

CooperScene: Multi-Modal Cooperative Autonomy Benchmark with C-V2X Communication Characterization

arXiv:2606.31219v1 Announce Type: new Abstract: Cellular vehicle-to-everything (C-V2X) enables cooperative perception, prediction, and planning beyond the field of view of individual agents. However,

DANTE-W: Diffuse Albedo Neural Texturing in the Wild

arXiv:2606.30677v1 Announce Type: cross Abstract: Classical mesh texturing techniques blend captured multi-view images directly, which inevitably suffer from baked-in shading and casted shadows that c

Diffusing Blame: Task-Dependent Credit Assignment in Biologically Plausible Dual-Stream Networks

arXiv:2606.31700v1 Announce Type: new Abstract: Biological neural circuits obey Dale's principle: each neuron's synapses are uniformly excitatory or inhibitory. Artificial networks that respect this c

Distilling Temporal Coherence into 2D Networks for Transrectal Ultrasound Prostate Video Segmentation

arXiv:2606.31198v1 Announce Type: cross Abstract: Real-time video segmentation of the prostate in Transrectal Ultrasound (TRUS) is essential for image-guided interventions. While conventional 2D metho

Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains

arXiv:2606.31342v1 Announce Type: cross Abstract: Partial differential equations on unbounded domains are challenging because the exterior region must be represented without excessive truncation error

Early-Terminable Energy-Safe Iterative Coupling for Parallel Simulation of Partitioned Port-Hamiltonian Systems

model-releasesarxiv-cs-ro

arXiv:2603.16424v2 Announce Type: replace Abstract: Parallel simulation of robotic systems requires partitioning the dynamics into coupled subsystems. Finite-iteration coupling across the partition bo

Editing Everything Everywhere All at Once

arXiv:2606.31278v1 Announce Type: new Abstract: Editing multiple elements of an image in a single forward pass is a practical alternative to multi-turn image manipulation, offering improved efficiency

ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies

arXiv:2606.31132v1 Announce Type: new Abstract: Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control.

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ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs

arXiv:2606.31982v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction prov

safetyarxiv-cs-cv

Local Ai

Event-Driven Video Generation

arXiv:2603.13402v3 Announce Type: replace Abstract: Current text-to-video models can make individual frames look convincing while still getting simple interactions wrong: objects move before contact,

local-aiarxiv-cs-cv

Evil Spectra: How Optimisers can Amplify or Suppress Emergent Misalignment

arXiv:2606.31591v1 Announce Type: cross Abstract: Emergent misalignment (EM) is a recently discovered phenomenon in LLMs where fine-tuning on a narrow misaligned task, such as writing insecure code, l

safetyarxiv-cs-ai

Local Ai

FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data

arXiv:2606.32023v1 Announce Type: cross Abstract: Forest attributes are essential for national-scale resource monitoring. Airborne LiDAR metrics are among the auxiliary variables most strongly correla

local-aiarxiv-cs-ai

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.30749v1 Announce Type: new Abstract: Large-scale dexterous grasp datasets encode rich priors over hand-object interaction, but their use has largely been confined to grasp generation and pi

Applications

From Materials Database to Materials Bank: Assetizing Data for AI Driven Materials Innovation

arXiv:2606.31366v1 Announce Type: cross Abstract: Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented r

applicationsarxiv-cs-ai

Generative Skill Composition for LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.32025v1 Announce Type: new Abstract: Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for perfor

Human-Agent Collaborative Paper-to-Page Crafting

arXiv:2510.19600v2 Announce Type: replace-cross Abstract: In the quest for scientific progress, communicating research is as vital as the discovery itself. Yet, researchers are often sidetracked by th

Tutorials

Human-as-Humanoid: Enabling Zero-Shot Humanoid Learning from Ego-Exo Human Videos with Human-Aligned Embodiments

arXiv:2606.32009v1 Announce Type: new Abstract: Vision-language-action (VLA) models across robot embodiments require high-quality observation--action supervision to learn deployable action distributio

tutorialsarxiv-cs-ro

HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space

arXiv:2606.31245v1 Announce Type: new Abstract: Surgical vision-language foundation models typically adopt educational materials, such as surgical lecture videos, to transfer surgical knowledge encode

researcharxiv-cs-cv

HyPOLE: Hyperproperty-Guided Multi-Agent Reinforcement Learning under Partial Observation

arXiv:2606.30966v1 Announce Type: new Abstract: Formal specification is a powerful tool to guide the learning process and provides significant advantages over reward shaping: (1) mathematical rigor; (

Tutorials

Improved Immiscible Diffusion: Accelerate Diffusion Training by Reducing Its Miscibility

arXiv:2505.18521v2 Announce Type: replace Abstract: The substantial training cost of diffusion models hinders their deployment. Immiscible Diffusion recently showed that reducing diffusion trajectory

tutorialsarxiv-cs-cv

Improving Certified Robustness via Adversarial Distillation

arXiv:2606.31653v1 Announce Type: cross Abstract: Certified training aims to produce models whose predictions can be formally verified against adversarial perturbations, typically by optimising upper

researcharxiv-cs-ai

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches

arXiv:2606.31363v1 Announce Type: new Abstract: Single image super-resolution aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs. Training SR models typically requires pai

safetyarxiv-cs-cv

Tutorials

Low-dimensional topology of deep neural networks

arXiv:2606.31856v1 Announce Type: new Abstract: We study layered models, including feedforward networks, ResNets, and transformers, by limiting each layer to a width of d = 3, i.e., R^3 as representat

tutorialsarxiv-cs-lg

LuxEmo: Expressive Text-to-Speech Corpus for Luxembourgish

model-releasesarxiv-cs-cl

arXiv:2606.31947v1 Announce Type: new Abstract: State-of-the-art speech datasets predominantly focus on widely spoken languages, often overlooking low-resource languages such as Luxembourgish, which r

NURBS Splatting: A Unified Differentiable Rendering Framework for Vector Graphics

arXiv:2606.31764v1 Announce Type: cross Abstract: Differentiable rendering of planar rational splines remains largely underexplored, despite their widespread use in vector graphics and design. Existin

On the Convergence of Self-Improving Online LLM Alignment

arXiv:2606.31524v1 Announce Type: cross Abstract: The Self-Improving Alignment (SAIL) algorithm addresses distribution shift by reducing a bilevel formulation of the problem to an efficient, single-le

One Reflection Is Not Enough: Self-Correcting Autonomous Research via Multi-Hypothesis Failure Attribution

arXiv:2606.31478v1 Announce Type: new Abstract: Autonomous research agents can now draft hypotheses, write code, run experiments, and produce papers, but they remain brittle when experiments fail. Und

OopsieVerse: A Safety Benchmark with Damage-Aware Simulation for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.31993v1 Announce Type: new Abstract: While robotic manipulation capabilities have advanced rapidly, physical safety remains a major barrier to deploying household robots: task success is in

Planar-SfM: Camera Pose Estimation via Homography Graph Embeddings

arXiv:2606.31979v1 Announce Type: new Abstract: Structure from Motion (SfM) systems traditionally struggle with planar scenes, where standard epipolar geometry-based methods become degenerate. Rather

PriorEye: Geospatial Visual Priors for End-to-End Autonomous Driving

arXiv:2606.31830v1 Announce Type: new Abstract: Most end-to-end autonomous driving methods rely solely on instantaneous sensor observations, limiting them to reactive behavior without the anticipatory

Private Rate-Constrained Optimization with Applications to Fair Learning

arXiv:2505.22703v2 Announce Type: replace Abstract: Many problems in trustworthy ML can be expressed as constraints on prediction rates across subpopulations, including group fairness constraints (dem

Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environments

arXiv:2507.18606v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as

researcharxiv-cs-lg

Quantum Flow Matching

arXiv:2508.12413v4 Announce Type: replace-cross Abstract: The flow matching has rapidly become a dominant paradigm in classical generative modeling, offering an efficient way to interpolate between tw

researcharxiv-cs-ai

Radial Suppression Accelerates Algorithmic Generalization: A Geometric Analysis of Delayed Generalization

arXiv:2606.32000v1 Announce Type: cross Abstract: Why do neural networks memorize algorithmic training data long before they generalize? We present a geometric case study demonstrating that, on tasks

Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs

arXiv:2606.32032v1 Announce Type: cross Abstract: Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhib

safetyarxiv-cs-ai

RESOLVE: A Multi-Resolution and Multi-Modal Dataset for Roadside Cooperative Perception

arXiv:2606.31895v1 Announce Type: new Abstract: LiDAR has increasingly been integrated into traffic cameras to expand coverage and mitigate occlusion in roadside cooperative perception. However, how u

Rethinking On-policy Optimization for Query Augmentation

arXiv:2510.17139v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have led to a surge of interest in query augmentation for information retrieval (IR). Two main appro

safetyarxiv-cs-cl

Revocable Learned State via Process Sidecars

arXiv:2606.30788v1 Announce Type: cross Abstract: Language models are often adapted in stages: a public skill phase, a private memory phase, and a later safety phase that learns to refuse outputs tied

safetyarxiv-cs-cl

RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents

arXiv:2606.22678v2 Announce Type: replace-cross Abstract: Agentic coding harnesses - such as Agent-Skills, Superpowers, and Agent-Rigor - are increasingly deployed to augment underlying LLMs for real-

Local Ai

Robust 3D-Masked Part-level Editing in 3D Gaussian Splatting with Regularized Score Distillation Sampling

arXiv:2507.11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.

local-aiarxiv-cs-ai

Same-Origin Policy for Agentic Browsers

arXiv:2606.14027v3 Announce Type: replace-cross Abstract: Agentic browsers integrate autonomous AI agents into web browsers, enabling users to accomplish web tasks through natural-language instruction

SENSE-VAD: Sentient and Semantic Video Anomaly Detection for Autonomous Driving

arXiv:2606.31875v1 Announce Type: new Abstract: Autonomous vehicles (AVs) must navigate not only motion-based hazards but also socially complex situations whose danger is constituted by inter-agent re

STEB: Style Text Embedding Benchmark

arXiv:2606.31741v1 Announce Type: cross Abstract: While semantic embeddings are rigorously evaluated on the Massive Text Embedding Benchmark, the evaluation of style embeddings remains fragmented, wit