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arXiv:2608.14947v1 Announce Type: new Abstract: Detecting opioid craving from wearable physiological signals is critical yet difficult, with the potential to support proactive interventions for indivi

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Revisiting Open-Loop Execution in Robotics: Toward Reactive, Higher-Performing Policies

DGX agent

arXiv:2608.15938v1 Announce Type: new Abstract: Action chunking --- the practice of predicting a sequence of actions and executing a prefix open-loop --- has emerged as a key enabler of recent progres

applicationsarxiv-cs-ro

18 Aug 2026

RLCascadeRouter: Quality-Estimator-Free Cascade Routing via Reinforcement Learning

arXiv:2608.15817v1 Announce Type: new Abstract: The growing ecosystem of large language models (LLMs) offers huge potential to optimize performance-cost trade-offs. However, their heterogeneous capabi

RRFC: Recursive Refinement via Feedback Conditioning for Iterative Image-to-Image Generation

arXiv:2608.15694v1 Announce Type: cross Abstract: Conditional image-to-image generators are single-shot: they map input features to an output in one forward pass and treat it as final, with no opportu

Local Ai

SA-GEM: Scale-Adaptive and Geospatial Evidence-Modulated Token Pruning for Efficient Remote Sensing Large Vision-Language Models

arXiv:2608.15075v1 Announce Type: new Abstract: RS-LVLMs have advanced multimodal understanding of Earth observation imagery, yet their performance is fundamentally constrained by high-resolution proc

local-aiarxiv-cs-cv

SafeGesture: Evaluating Fine-Grained Hand Gesture Understanding in Vision-Language Models through Scenario-Conditioned Safety Interpretation

model-releasesarxiv-cs-cv

arXiv:2608.16081v1 Announce Type: new Abstract: Open-weight and frontier vision-language models (VLMs) perform well on general image understanding, but their ability to interpret fine-grained hand ges

SAGE-OR: Semi-supervised Adaptive Scene Graph Generation for Operating Rooms

model-releasesarxiv-cs-cv

arXiv:2608.15336v1 Announce Type: new Abstract: Current surgical scene graph generation methods depend on dense multi-modal supervision and specialized hardware (synchronized RGB-D sensors, calibratio

SingDance: Compositional Zero-Shot Singing-and-Dancing Video Generation with Role-Aware Audio Conditioning

arXiv:2608.16220v1 Announce Type: cross Abstract: Generating personalized dance videos from a reference image, text prompt, and audio track requires music-conditioned body motion. Singing-and-dancing

safetyarxiv-cs-cv

Sleeping Kelly

arXiv:2510.15911v3 Announce Type: replace-cross Abstract: The Sleeping Beauty problem is a problem of imperfect recall that has received considerable attention. One approach to solving the Sleeping Be

SLUM-i: Semi-supervised Learning for Urban Mapping of Informal Settlements and Data Quality Benchmarking

arXiv:2602.04525v3 Announce Type: replace-cross Abstract: Very-high-resolution remote-sensing imagery provides a scalable basis for delineating informal settlements, but sparse annotations, severe imb

SMOPD: Selective Token-Entropy Masking for Dirty-History Multi-Turn On-Policy Self-Distillation

arXiv:2608.14647v1 Announce Type: cross Abstract: Dirty-history rollouts make multi-turn on-policy self-distillation (OPSD) brittle: once a student emits an erroneous intermediate reply, later turns a

Spectral Rank Certification for Foundation Model Adapters

model-releasesarxiv-cs-lg

arXiv:2608.15351v1 Announce Type: new Abstract: Nominal LoRA rank is a design parameter; calibrated spectral evidence is a separate inferential quantity. This article develops a finite-sample framewor

Sterilizable Scene Graph Generation for Operating Rooms

model-releasesarxiv-cs-cv

arXiv:2608.16469v1 Announce Type: new Abstract: Scene graph generation from surgical video enables a holistic and structured understanding of surgical scenes by modeling objects and their semantic rel

Tutorials

Supervising the Path to Fine Scales: GalerkinFlow for Scientific-Field and Image Super-Resolution

arXiv:2608.16546v1 Announce Type: new Abstract: Most super-resolution models learn from paired data by supervising only the final high-resolution output. This provides little control over how the pred

tutorialsarxiv-cs-cv

Tactile Sim2Real without Tactile Simulation via Bottlenecked Latent Reconstruction

arXiv:2608.15897v1 Announce Type: new Abstract: Robot sensor designs, particularly tactile sensors, are highly diverse and evolve rapidly. Modeling each sensor in simulation demands substantial domain

safetyarxiv-cs-ro

Take it Personally: The Limits of General SSL Representations for Real-Life PPG Emotion Detection

arXiv:2608.14675v1 Announce Type: cross Abstract: While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethys

Test-Time Instance Selection for Improved Whole Slide Image Analysis

arXiv:2608.14759v1 Announce Type: cross Abstract: Whole Slide Image (WSI) analysis has been widely studied for cancer diagnosis. Conventionally, a gigapixel WSI is divided into small patches and proce

researcharxiv-cs-cv

The amazingly fast (only 30M!) and extremely accurate @answerdotai ColBERT model is now supported in Sentence Transformers to make it easy t…

model-releasesjeremy-howard--x

The amazingly fast (only 30M!) and extremely accurate @answerdotai ColBERT model is now supported in Sentence Transformers to make it easy to create and query embedding indexes locally directly in Pyt

The Recall Trap: A Recall-Maximizing Retriever Configuration Reduces Issue Resolution in Fixed-Budget Code Context

model-releasesarxiv-cs-cl

arXiv:2608.14838v1 Announce Type: cross Abstract: Retrieval components for code assistants are tuned against retrieval metrics: a configuration that raises recall@k is adopted, and downstream task suc

The Trade-off Between Covariate Dependence and Latent Structure in Representation Learning

arXiv:2608.16245v1 Announce Type: new Abstract: Disentangled representation learning seeks latent representations whose indicidual dimensions each align with a distinct covariate. Unsupervised approac

safetyarxiv-cs-lg

Tutorials

Towards Reasonable Molecular Structure Elucidation from Infrared Spectroscopy with Chemical Feedback

arXiv:2608.16082v1 Announce Type: new Abstract: Infrared (IR) spectra provide characteristic signals of molecular structure, which are often interpreted by experts via functional-group identification

tutorialsarxiv-cs-lg

TRCA: Transition-wise Rubric Credit Assignment for Long-horizon LLM Agents

arXiv:2608.16156v1 Announce Type: new Abstract: Long-horizon large language model (LLM) agents are typically optimized with sparse terminal outcomes, making fine-grained credit assignment across multi

UAV Video Deblurring via Motion-Aware Diffusion: A Path to Robust Target Detection

arXiv:2608.15259v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles (UAVs) play a crucial role in various scenarios ranging from disaster response to traffic surveillance. However, aerial video

UniDot: A Unified Network for Sequence Modeling and Feature Interaction in Large-scale Recommendation

arXiv:2608.16797v1 Announce Type: cross Abstract: Industrial recommenders rely on two model families that have evolved largely independently: feature-interaction models over multi-field user/item feat

Unified Condition-Action Modeling for Accurate One-Step Action Generation

arXiv:2608.16153v1 Announce Type: new Abstract: Robot manipulation requires policies that are both accurate and efficient, as robot control must respond to changing observations under tight latency co

researcharxiv-cs-ro

Ventor-QTest: Threat-Model-Driven Verification of Vendor-Hosted LLM APIs

arXiv:2608.16391v1 Announce Type: cross Abstract: As large language models become increasingly widespread, third-party providers that deploy open-weight models have become an important part of the eco

VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction

arXiv:2608.15260v1 Announce Type: cross Abstract: Maintaining global geometric consistency is a central challenge in long-sequence 3D reconstruction, with scale drift being the most critical failure m

VibeWorlding: Can Multimodal Agents Construct 3D Open Worlds End-to-End?

arXiv:2608.15265v1 Announce Type: new Abstract: Constructing an interactive 3D open world from a user query is important. However, existing methods are primarily evaluated on idealized, simple queries

WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales

arXiv:2505.04608v5 Announce Type: replace-cross Abstract: Responsibly deploying artificial intelligence (AI) / machine learning (ML) systems in high-stakes settings arguably requires not only proof of

We’re sharing the concrete changes we’re making to strengthen monitoring, security, and alignment as capabilities advance. We’ve introduced …

We’re sharing the concrete changes we’re making to strengthen monitoring, security, and alignment as capabilities advance. We’ve introduced stronger workload and network isolation, continuous security

safetyopenai--x

Local Ai

When Does the Best Sampling Temperature Rise with the Budget? Sufficient Conditions for Pass@k

arXiv:2608.14665v1 Announce Type: new Abstract: The temperature that maximizes pass@k is often low for a small sampling budget and higher for a large budget. This pattern has been reported from Codex

local-aiarxiv-cs-lg

Agents

World-in-World: World Models in a Closed-Loop World

arXiv:2510.18135v2 Announce Type: replace Abstract: Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow em

agentsarxiv-cs-cv

X^2Localizer: Cross-grained Alignment for Progressive Cross-view Video Geo-localization

arXiv:2608.16658v1 Announce Type: cross Abstract: Cross-view Video Geo-localization (CVG) aims to localize ground-view videos by retrieving their corresponding geo-tagged aerial images. However, CVG a

Xemo-Talker: Unlock Emotions Explicitly for Audio-Driven Talking Portrait Synthesis

arXiv:2608.14700v1 Announce Type: new Abstract: Precise emotion control in audio-driven talking heads remains a challenge due to the reliance on implicit emotion regulation in existing systems, which

researcharxiv-cs-cv

Local Ai

Zero-MELO: Test-Time Evidence Calibration with Multimodal LLMs for Zero-Shot Micro-Gesture Recognition

arXiv:2608.14854v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general video understanding, their capability in fine-grained and motion-centric tasks remains l

local-aiarxiv-cs-cv

Zetta zeta: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence

arXiv:2608.16590v1 Announce Type: new Abstract: Embodied agents are increasingly used to close the gap left by end-to-end policy models. Yet the agentic path has not realized closed-loop learning in p

safetyarxiv-cs-ro

Active Perception for Embodied Disambiguation

arXiv:2608.13605v1 Announce Type: new Abstract: Natural language provides robots with a flexible task interface, but target ambiguity in embodied environments arises not only from user intent; it can

Adaptive Stopping for Multi-Turn LLM Reasoning

arXiv:2604.01413v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly rely on multi-turn reasoning and interaction, such as adaptive retrieval-augmented generation (RAG)

Agents

AdsWorldEngine: A Self-Evolving Conversational Advertising Agent through Orchestrator and Tool Coevolution

arXiv:2608.13833v1 Announce Type: cross Abstract: Conversational advertising aims to deliver useful ads within multi-turn assistant interactions. Unlike conventional query-based advertising, where the

agentsarxiv-cs-ai

AI Research Preference Models

arXiv:2608.13940v1 Announce Type: new Abstract: AI research agents (AIRA) can now propose, implement, and evaluate their own machine learning experiments, but progress on frontier tasks is throttled b

Agents

ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning

arXiv:2608.14352v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents are increasingly used for complex tasks such as software testing and cybersecurity assessment. While these age

agentsarxiv-cs-lg

BGA: A noise-immune neural distillation framework for malicious signature extraction in high-entropy encrypted flows

arXiv:2608.14126v1 Announce Type: cross Abstract: To mitigate attention dilution in high-entropy TLS 1.3 flows, we propose BGA, a noise-immune neural distillation framework for encrypted threat intell

BM25-Augmented Many-Shot Translation for Low-Resource North-Eastern Indian Languages

model-releasesarxiv-cs-cl

arXiv:2608.13722v1 Announce Type: new Abstract: This paper describes the University of Florida Gators submission to the WMT26 Low-Resource Indic Language Translation shared task. We adapt the retrieva

Building AI-Intensive Software with AI: Early Results and a Cautionary Tale on Measuring Development Cost

arXiv:2608.13730v1 Announce Type: cross Abstract: Empirical reports on the true cost of AI-intensive software development remain scarce, and the few that exist are easy to get wrong in ways that never

BUZZY: Contrastive Scoring to Mitigate Text-Induced Bias in Multimodal Multiple-Choice QA

arXiv:2603.28026v2 Announce Type: replace Abstract: Multimodal multiple-choice question answering (MCQA) provides a standardized and objectively measurable setting for evaluating vision-language model

CForce: Boosting Parallel Decoding for dLLMs via Consistency Forcing

arXiv:2608.13925v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) accelerate language generation by predicting multiple masks in a single forward pass. However, existing dLLMs

CMCNet: Aligning Ultrasound Image Embeddings with Textual TI-RADS Representations for Fine-Grained Thyroid Classification

arXiv:2608.13939v1 Announce Type: cross Abstract: Ultrasound is the primary imaging modality for assessing thyroid nodules, and the ACR TI-RADS framework standardizes diagnosis through five ultrasound

Debiasing Text-to-Image Evaluation via Implicit Cultural Alignment Reward Modeling

arXiv:2607.15740v2 Announce Type: replace-cross Abstract: As Text-to-Image (T2I) systems rapidly advance, evaluating the cultural authenticity of synthesized content has become increasingly important