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Huge congratulations to @JeffDean and the legendary founding team on the launch! 🚀 I share a deep conviction in this mission. Automating th…

Huge congratulations to @JeffDean and the legendary founding team on the launch! 🚀 I share a deep conviction in this mission. Automating the scientific method will profoundly alter the trajectory of A

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Research

Imitation Learning from Human Motion Alone Does Not Guarantee Biomechanically Plausible Gait Kinetics

DGX agent

arXiv:2603.12408v3 Announce Type: replace-cross Abstract: Motion imitation learning (IL) is increasingly used in robotics and human gait modeling, yet its ability to recover biomechanically consistent

researcharxiv-cs-lg

6 Aug 2026

Introducing Kitesurf: The agent-first browser that runs in V8 isolates on Cloudflare Workers

We should be giving all agents tools that excel at what’s important for an AI model. Kitesurf is Cloudflare’s new stateless, highly scalable, and cost-effective web browser that runs entirely on top o

agentscloudflare-ai

Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks

arXiv:2608.04027v1 Announce Type: new Abstract: This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neu

LLMs Struggle to Measure What Distinguishes Students of Different Proficiency Levels: A Study of Item Discrimination in Reading Comprehension Assessment

arXiv:2606.18709v2 Announce Type: replace Abstract: Existing work on LLM-based educational assessment has focused largely on item difficulty, but difficulty alone does not indicate whether an item mea

safetyarxiv-cs-cl

Local Violation Certification for Linear Predict-Then-Optimize Pipelines

arXiv:2608.04474v1 Announce Type: new Abstract: Data-driven decision pipelines combining predictive machine learning models with downstream optimization software are increasingly used to make high-sta

MALT: Lightweight Curvature-Aware Muon via Diagonal Preconditioning

arXiv:2608.05088v1 Announce Type: new Abstract: Muon has recently emerged as a promising alternative to AdamW for language model pretraining by orthogonalizing momentum matrices using Newton-Schulz it

researcharxiv-cs-lg

Masked diffusion enables coherent beat tracking

arXiv:2608.04624v1 Announce Type: cross Abstract: Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not p

MemFly: On-the-Fly Memory Optimization via Information Bottleneck

arXiv:2602.07885v2 Announce Type: replace Abstract: Long-term memory enables large language model agents to tackle complex tasks through historical interactions. However, existing frameworks encounter

Multi-View Face and Gesture Animation with Dynamic Gaussians

arXiv:2608.04722v1 Announce Type: new Abstract: Creating photorealistic 3D human avatars with realistic upper-body motion remains challenging. Existing approaches either focus on the head and overlook

MVTOP: Multi-View Transformer-based Object Pose-Estimation

arXiv:2508.03243v2 Announce Type: replace Abstract: We present MVTOP, a novel transformer-based method for multi-view rigid object pose estimation. Through an early fusion of the view-specific feature

Tutorials

NeuMoSync: End-to-End Neuromodulatory Control for Plasticity and Adaptability in Continual Learning

arXiv:2608.04358v1 Announce Type: new Abstract: Continual learning (CL) requires models to learn tasks sequentially, yet deep neural networks often suffer from plasticity loss and poor knowledge trans

tutorialsarxiv-cs-ai

ODRA: Synthesizing Cognitive Behavioral Therapy Sessions with Structured Chain-Of-Thought and Dynamic Patient Resistance

arXiv:2608.04524v1 Announce Type: new Abstract: Synthetic generation of Cognitive Behavioral Therapy (CBT) sessions is challenged by two competing demands: adhering to strict therapeutic structure whi

safetyarxiv-cs-cl

Promptable Animal Pose Tracking Across Species

arXiv:2608.04995v1 Announce Type: new Abstract: Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated

local-aiarxiv-cs-cv

Pun Intended: Multi-Agent Translation of Wordplay with Contrastive Learning and Phonetic-Semantic Embeddings for CLEF JOKER 2025 Task 2

arXiv:2507.06506v2 Announce Type: replace-cross Abstract: Translating wordplay across languages presents unique challenges that have long confounded both professional human translators and machine tra

Q-CueGraph: Query-Conditioned Visual Evidence Graphs for Multimodal Reasoning

arXiv:2608.04452v1 Announce Type: cross Abstract: High-resolution pixels and crop or zoom tools give multimodal large language models the ability to inspect an image, but they do not provide a reliabl

safetyarxiv-cs-ai

Real-time probabilistic tsunami forecasting via generative AI

arXiv:2608.04327v1 Announce Type: new Abstract: Explicit onshore tsunami inundation forecasting can improve public risk awareness, but deterministically predicted inundation boundaries under highly un

Risk Is Not the Target: A Monotonic Framework for Evaluating Wildfire Operational Risk Signals

arXiv:2607.21597v2 Announce Type: replace Abstract: Evaluating wildfire risk systems using standard machine-learning metrics such as F1-score or IoU is fundamentally flawed: these metrics assess event

local-aiarxiv-cs-ai

Seeking Physics in Diffusion Noise

arXiv:2603.14294v3 Announce Type: replace-cross Abstract: Do video diffusion models encode signals predictive of physical plausibility? We probe intermediate denoising representations of pretrained Di

Sequential Kernel-based Conditional Independence Testing via Adaptive Betting

arXiv:2606.18993v2 Announce Type: replace-cross Abstract: Testing conditional independence is fundamental yet intrinsically difficult: without additional assumptions, Type I error control is impossibl

SHIELD: A Segmented Hierarchical Memory Architecture for Energy-Efficient LLM Inference on Edge NPUs

arXiv:2604.07396v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) inference on edge Neural Processing Units (NPUs) is fundamentally constrained by limited on-chip memory capacity. A

researcharxiv-cs-lg

Tutorials

SJEPA: Learning Elegant Latent Dynamics with Hybrid Symbolic-Neural Predictors

arXiv:2608.04060v1 Announce Type: cross Abstract: Joint-embedding predictive architectures learn abstract states by predicting target embeddings from context embeddings, but their transition models ar

tutorialsarxiv-cs-ai

Structured LLM Reasoning for Zero-Shot Human--Robot Coordination Under Hidden Goals

arXiv:2608.04309v1 Announce Type: new Abstract: We present a structured large-language-model (LLM) architecture for zero-shot human--robot coordination in a cooperative construction task with private

safetyarxiv-cs-ro

Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling

arXiv:2608.04230v1 Announce Type: cross Abstract: Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful mu

TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction

arXiv:2608.04453v1 Announce Type: cross Abstract: Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map con

Applications

Visualizing Graph-to-Answer Mechanism Recovery in Materials-Science Hypothesis Generation

arXiv:2608.04170v1 Announce Type: cross Abstract: AI co-scientists can generate fluent materials-science hypotheses, but fluency does not show that an answer preserves a scientifically meaningful mech

applicationsarxiv-cs-ai

When Memory Lies: An Empirical Study of Spatial Memory Staleness in VLM Agents

arXiv:2608.04574v1 Announce Type: new Abstract: Memory-augmented VLM agents act on persistent spatial knowledge, yet that knowledge silently goes stale as the environment changes. We ask what happens

safetyarxiv-cs-cl

A Theory of Conditional Collapse under Low-Rank Weight-Space Ablations: I. The Single-Block Theory and Synthetic Validation

arXiv:2608.03620v1 Announce Type: cross Abstract: Activation patching and weight-space ablation both claim a component is causally responsible for a behavior, yet they act on different objects: one fo

Agent memory layers don't need an LLM deciding what to remember

Most agent memory setups run a model call on the way in. Something reads the turn, decides whether it's worth keeping, rewrites it into a 'memory', tags it with a type and an importance score. That's

local-air-localllama

AgenticVAU: Multi-Agent Explore-Verify Reasoning for Video Anomaly Understanding

arXiv:2608.03779v1 Announce Type: new Abstract: Video anomaly understanding (VAU) focuses on comprehensively interpreting abnormal events in videos, requiring models to identify anomalous occurrences,

local-aiarxiv-cs-cv

AIDE: Automated Instruction via Distilled Expertise for Reference-Free Motor Skill Coaching

arXiv:2608.03047v1 Announce Type: new Abstract: Generating natural-language coaching feedback on motor skills can accelerate learning, yet expert coaches are scarce and expensive. Existing reference-b

Behaviorally Adaptive Visual Diversion for Inclusive and Resilient Digital Assessment Delivery

arXiv:2608.03531v1 Announce Type: new Abstract: Institutions increasingly rely on browser lockdown, webcam monitoring, and behavioral analytics to secure high-stakes digital assessments, yet these mec

Applications

Benchmarking the Benchmarks: Testing the Predictive Validity of Commonsense Benchmarks

arXiv:2608.03340v1 Announce Type: new Abstract: Predicting LLM's capabilities on real-world tasks is essential, yet the extent to which performance on commonsense benchmarks predicts downstream perfor

applicationsarxiv-cs-cl

Benign interpolation and Occam's razor

arXiv:2608.03386v1 Announce Type: new Abstract: Contemporary deep learning methods generalize well even when they fit their training data perfectly, a phenomenon known as benign interpolation. This ph

researcharxiv-cs-lg

Best experience with MCP UE 5.8

Hey. I'm very limited with brain capacity and I'm new to this. If you have experience, tell me which local model fits the best, what makes best blueprints etc. For example I want to spawn enemies usin

local-air-ollama

Applications

Beyond Average Performance: Dynamic Instance Clustering and Specialized Algorithm Design in LLM-Assisted Evolutionary Search

arXiv:2608.03129v1 Announce Type: new Abstract: Large Language Model-assisted Evolutionary Search (LES) has emerged as a powerful paradigm for automated algorithm design. However, existing LES methods

applicationsarxiv-cs-ai

CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement

arXiv:2608.03890v1 Announce Type: cross Abstract: A clinically useful chest X-ray system must go beyond fluent report generation: it should classify findings with tunable decision thresholds, localize

local-aiarxiv-cs-ai

Character Iconicity vs. Arbitrariness: An Arabic NLP Perspective

arXiv:2608.02935v1 Announce Type: new Abstract: Arabic script uses 28 letters, many of which share a common base shape (rasm) and are distinguished only by dot placement. Because early Arabic manuscri

researcharxiv-cs-cl

Hardware

Compound and Parallel Modes of Tropical Convolutional Neural Networks

arXiv:2504.06881v2 Announce Type: replace-cross Abstract: Convolutional neural networks (CNNs) are foundational to many state-of-the-art computer vision systems, yet their reliance on multiplication-i

hardwarearxiv-cs-ai

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution

arXiv:2608.03483v1 Announce Type: cross Abstract: Existing chunk-based Vision-Language-Action (VLA) models execute a fixed number of actions (i.e., execution horizon) before replanning, turning replan

safetyarxiv-cs-ai

DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers

arXiv:2608.03082v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled remarkable progress in visual synthesis, benefiting from their superior scalability. To fa

safetyarxiv-cs-cv

DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

arXiv:2608.03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneo

safetyarxiv-cs-ai

Don't Regenerate, Debug: A Domain-Specific Agent for Repairing Near-Miss Hardware Operators

arXiv:2608.02712v1 Announce Type: cross Abstract: Kernel generation for hardware accelerators such as GPUs and NPUs has become a proving ground for large language models (LLMs), and state-of-the-art s

DRIFT: Derailing Denoising Trajectories of Flow-Matching VLAs with Adversarial Patch Attack

arXiv:2608.03207v1 Announce Type: new Abstract: Flow-matching vision-language-action (VLA) models such as pi0 generate robot actions by integrating a learned denoising velocity field, and have been re

safetyarxiv-cs-cv

Enhancing Q-Value Updates in Deep Q-Learning via Successor-State Prediction

arXiv:2511.03836v2 Announce Type: replace Abstract: Deep Q-Networks (DQNs) estimate future returns by learning from transitions sampled from a replay buffer. However, the target updates in DQN often r

Equivariant Music Transformer

arXiv:2608.03920v1 Announce Type: cross Abstract: Humans recognize a musical passage even when it is shifted in time or transposed in pitch, indicating a notion of equivariance in the representation s

Formal Verification of Agentic Systems over Operational Data

arXiv:2608.03609v1 Announce Type: new Abstract: Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data.

FraQ: Efficient Coordinate-Space Recompression for Federated Low-Rank Adaptation

arXiv:2608.03605v1 Announce Type: new Abstract: Federated fine-tuning with Low-Rank Adaptation (LoRA) enables efficient collaborative adaptation of Large Language Models (LLMs) without centralizing pr