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Two AI Metrics Diverged: Will it Make All the Difference?

arXiv:2607.00913v1 Announce Type: new Abstract: As exponential compute scaling continues, will the capabilities of frontier AI models outstrip what is accessible to developers on a small fixed budget?

Understanding Why Language Models Hallucinate: Testing Reasoning Against Priors

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arXiv:2607.00447v1 Announce Type: new Abstract: Large language models often produce hallucinated answers that violate prompt-level constraints. A key diagnostic question is whether these failures refl

safetyarxiv-cs-cl

2 Jul 2026

Unleashing More Actions via Action Compositional Training for VLA Models

arXiv:2607.00351v1 Announce Type: new Abstract: Vision-Language-Action models excel at robotic manipulation, driven by the scale and diversity of demonstration data. However, standard training paradig

Verifiable Rewards for Calibrated Probabilistic Forecasting

arXiv:2607.00164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards can in principle train calibrated probabilistic forecasters, since a proper scoring rule such as the Brie

VideoSearch-R1: Iterative Video Retrieval and Reasoning via Soft Query Refinement

arXiv:2607.00446v1 Announce Type: cross Abstract: As video corpora continue to expand in both scale and task complexity, there is increasing demand for approaches that retrieve relevant videos from la

What to expect during the Machina AI summit: Join theCUBE July 7

Physical artificial intelligence is becoming an industrial robotics problem. The market is shifting from software-only automation toward machines that must sense, decide and act in physical settings.

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When to Personalize Household Object Search: A Rigidity-Gated Hybrid Policy

arXiv:2607.00022v1 Announce Type: new Abstract: Service robots searching for household objects rely on spatial priors to reduce search cost, yet object locations can vary with resident traits. Collect

Would You Marry Superintelligence?

arXiv:2607.00120v1 Announce Type: cross Abstract: Emotional bonds between humans and AI companions are growing, and the question of whether a person may marry an AI system will soon move from speculat

Zero-Shot Distracted Driver Detection via Vision Language Models with Double Decoupling

arXiv:2601.08467v2 Announce Type: replace Abstract: Distracted driving is a major cause of traffic collisions, calling for robust and scalable detection methods. Vision-language models (VLMs) enable s

3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance

arXiv:2606.31329v1 Announce Type: cross Abstract: Hierarchical Vision-Language-Action (VLA) models decouple high-level planning from low-level control to improve generalization in robot manipulation.

A basic sigmoid extrapolation suggests that this measurement will be close to its performance ceiling in around a year---meaning most random…

A basic sigmoid extrapolation suggests that this measurement will be close to its performance ceiling in around a year---meaning most randomly sampled remote work projects would be highly automatable

safetydan-hendrycks--x

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems

arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ

A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting

arXiv:2509.15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abun

A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning

arXiv:2602.20062v2 Announce Type: replace Abstract: Pretraining and fine-tuning are central stages in modern machine learning systems. In practice, feature learning plays an important role across both

A Tutorial on Autonomous Fault-Tolerant Control Using Knowledge-Grounded LLM Agents

arXiv:2606.31635v1 Announce Type: cross Abstract: Fault recovery in process plants still relies heavily on plant operators, especially when faults fall outside predefined supervisory logic. Operators

AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation

arXiv:2606.31204v1 Announce Type: new Abstract: Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demons

ADAPT: Attention Dynamics Alignment with Preference Tuning for Faithful MLLMs

arXiv:2606.31054v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are critically hampered by hallucination, generating content inconsistent with the provided image. In this pa

Adapting Generalist Robot Policies with Semantic Reinforcement Learning

arXiv:2606.31958v1 Announce Type: new Abstract: Generalist robot policies learn a diverse repertoire of behaviors from large-scale pretraining. In principle, this makes them excellent priors for downs

Addressing Over-Refusal in LLMs with Competing Rewards

arXiv:2606.31748v1 Announce Type: new Abstract: Safety training on language models often induces over-refusal: improved safety on harmful prompts at the cost of increased refusal on harmless ones. Tho

AeroVerse-SatAgent: UAV-Satellite Collaborative Spatial Reasoning Inspired by the Dual Visual Pathway Theory of Cognitive Neuroscience

arXiv:2606.31467v1 Announce Type: new Abstract: With the rapid advancement of aerospace embodied intelligence, enabling Unmanned Aerial Vehicles (UAVs) to autonomously understand and reason about comp

AETDICE: Unified Framework and Offline Optimization for Nonlinear Multi-Objective RL

arXiv:2606.31178v1 Announce Type: cross Abstract: Optimizing nonlinear preferences in multi-objective reinforcement learning (MORL) is essential for capturing complex trade-offs like risk aversion or

AI for Quality Assurance in the Operating Room

arXiv:2606.30657v1 Announce Type: cross Abstract: Surgical outcomes depend not only on patient factors and postoperative care but are also strongly influenced by the quality of the operation itself. Y

AI systems that are accessible or even better open-source are safer for a simple reason: more people can inspect them, test them, stress the…

AI systems that are accessible or even better open-source are safer for a simple reason: more people can inspect them, test them, stress them, and report what breaks or harms to keep the builders acco

safetyclem-delangue--x

AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model

arXiv:2606.19100v2 Announce Type: replace Abstract: Large Vision and Language Models (LVLMs) have advanced rapidly, yet European Portuguese (pt-PT) remains systematically underserved by existing open-

Analysis of Atomic Charge State and Atomic Number for VAMOS++ Magnetic Spectrometer using Deep Neural Networks and Fractionally Labelled Events

arXiv:2507.07109v2 Announce Type: cross Abstract: The VAMOS++ magnetic spectrometer is a multi-parametric system that integrates ion optical magnetic elements with a multi-detector stack. The magnetic

Anchoring on Reality: Breaking the Pseudo-Target Ceiling in Makeup Transfer

arXiv:2606.31089v1 Announce Type: new Abstract: Makeup transfer applies a reference cosmetic style to a source face while preserving its identity and geometry. However, this task is severely hindered

AR-CoPO: Align Autoregressive Video Generation with Contrastive Policy Optimization

arXiv:2603.17461v2 Announce Type: replace Abstract: Streaming autoregressive (AR) video generators combined with few-step distillation achieve low-latency, high-quality synthesis, yet remain difficult

Ask the World Before Acting: Budgeted Environment Probing for World-Model Calibration

arXiv:2606.31422v1 Announce Type: new Abstract: Long-horizon language agents do not only choose actions; they carry a private model of the world from one decision to the next. When that model drifts,

Automating Cause-Effect Specification with Knowledge Graphs and Large Language Models

arXiv:2606.31614v1 Announce Type: cross Abstract: Engineering specifications such as interlocks, alarm rationalization tables, and cause-and-effect (C&E) matrices remain central to process control and

Autonomous UAV Navigation for Individual Wildlife Re-Identification

arXiv:2606.31772v1 Announce Type: new Abstract: Reliable individual re-identification (re-ID) of wildlife is essential for population monitoring, behavioral tracking, and conservation policy evaluatio

AVTok: 1D Unified Tokenization for Holistic Audio-Video Generation

arXiv:2606.30811v1 Announce Type: new Abstract: Audio-video generation has recently gained unprecedented research attention, aiming to synthesize high-quality sounding video content with fine-grained

Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback

arXiv:2606.30923v1 Announce Type: cross Abstract: Imitation Learning is a natural framework for learning in sequential decision-making systems and has emerged as the dominant paradigm through which we

Beyond the Expressivity-Trainability Paradox: A Dynamical Lie Algebra Perspective on Navigating Barren Plateaus in Quantum Machine Learning

arXiv:2606.31536v1 Announce Type: new Abstract: As Quantum Machine Learning (QML) transitions toward practical implementation, the field faces a critical architectural bottleneck that challenges the f

BlockPilot: Instance-Adaptive Policy Learning for Diffusion-based Speculative Decoding

arXiv:2606.31315v1 Announce Type: new Abstract: Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in parallel, and are then verified by the tar

safetyarxiv-cs-cl

BP-TTA: Balanced and Prototype-Guided Test-Time Adaptation in Dynamic Scenarios

arXiv:2606.31420v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enables models trained on a source domain to adapt online to unlabeled test data under distribution shifts. While recent TTA

Breaking Failure Cascades: Step-Aware Reinforcement Learning for Medical Multimodal Reasoning

arXiv:2606.31825v1 Announce Type: cross Abstract: Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantl

Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration

arXiv:2601.19506v4 Announce Type: replace Abstract: Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrai

Can Tabular In-Context Learners Generalize to Biomolecular Property Prediction?

arXiv:2606.31126v1 Announce Type: new Abstract: Predicting biomolecular properties from limited labeled data is a central bottleneck in protein engineering and small-molecule design. As strong pretrai

CasaMaestro: Multi-View Panoramas for House-Scale 3D Reconstruction

arXiv:2606.31086v1 Announce Type: new Abstract: The rise of home-deployed embodied AI systems is driving a growing need for fast, metric 3D reconstruction of residential spaces to support navigation,

Certified Speculative Execution for Untrusted AI Agents

arXiv:2606.31023v1 Announce Type: cross Abstract: Hard-constrained sequential decision systems have no certified way to spend the test-time compute of modern AI: executing the multi-step drafts of a l

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

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

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

CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac

Corruption Robust Offline Reinforcement Learning with Human Feedback

arXiv:2402.06734v2 Announce Type: replace-cross Abstract: We study data corruption robustness for reinforcement learning with human feedback (RLHF) in an offline setting. Given an offline dataset of p

Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers

arXiv:2606.32020v1 Announce Type: new Abstract: Modern one-step diffusion models achieve impressive quality through distribution-based timestep distillation. Yet, they rely on a critical assumption: T

DataEvolver: Self-Evolving Multi-Agent Data Construction for Text-Rich Image Generation

arXiv:2606.31537v1 Announce Type: new Abstract: Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic imag

DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction

arXiv:2606.31085v1 Announce Type: new Abstract: Drug-drug interaction (DDI) prediction is essential for medication safety, yet it requires reasoning over heterogeneous biomedical evidence whose releva

Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry

arXiv:2606.31291v1 Announce Type: new Abstract: Deep reinforcement learning has the potential to solve attitude control problems more adaptively, precisely, and robustly by handling nonlinear dynamics