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Flowing Faster to Coordinate: One-Step Online Multi-Agent Flow Policies

arXiv:2610.01882v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment.

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FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering

DGX agent

arXiv:2603.04349v2 Announce Type: replace Abstract: Understanding long videos is crucial for embodied intelligent agents, as their performance depends on effectively accumulating and using long-horizo

researcharxiv-cs-cv

2 Oct 2026

Fold'EM: Direct atomic structure inference from Cryo-EM particles

arXiv:2610.01358v1 Announce Type: cross Abstract: Single-particle cryo-electron microscopy (cryo-EM) has become a widely adopted technique for biomolecular structure determination. The conventional cr

Industry

For folks not understanding where we are at with AI now - if the task is verifiable, it is now solved by AI. Yes, earlier days you could arg…

For folks not understanding where we are at with AI now - if the task is verifiable, it is now solved by AI. Yes, earlier days you could argue that 'AI isn't that good' (e.g. see first attached chart

industryelon-musk--x

FORALL-LEAN-AGENT for Auditable Reasoning in Formal Mathematics and Software Verification

model-releasesarxiv-cs-ai

arXiv:2610.00885v1 Announce Type: cross Abstract: Coding agents increasingly automate Lean proof development, but successful compilation alone does not establish that a candidate proves the intended s

Forking: Sudden Overfitting Under Replay

arXiv:2610.00394v1 Announce Type: new Abstract: This paper studies forking, a generalization failure discovered in NanoGPT autoresearch. Under data replay, models with an over-encoding n-gram memory b

Agents

Form and Void: Entangled Composition through an Autonomous AI Agent

arXiv:2610.02045v1 Announce Type: new Abstract: Positive and negative space is a fundamental principle in visual composition, supporting visually coherent forms and layered semantic relationships. Gen

agentsarxiv-cs-cv

Format-Aware Fusion for Fast FP4 Pretraining

arXiv:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved back

FORTE: Adaptive Scoring and Exact Keyframe Selection for Long-Video Question Answering

arXiv:2610.00573v1 Announce Type: new Abstract: Query-aware keyframe selection enables multimodal large language models (MLLMs) to process long videos using only a small set of question-relevant frame

researcharxiv-cs-cv

Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses

arXiv:2506.11030v2 Announce Type: replace-cross Abstract: Training neural networks has traditionally relied on backpropagation (BP), a gradient-based algorithm that, despite its widespread success, su

Foundations without Fundamentals: Zero-Shot Blind Spots in Time Series FMs

arXiv:2610.02058v1 Announce Type: new Abstract: Despite the success of Time Series Foundation Models (TSFMs) on broad benchmarks, their ability to internalize basic temporal logic, especially in setti

applicationsarxiv-cs-lg

Tutorials

Four Ways to Grow a Classifier and Why One of Them Cannot Learn

arXiv:2610.00180v1 Announce Type: cross Abstract: Constructive classifiers add structure while they train: a level to a tree, a unit to a hidden layer, a split at a leaf. This paper asks what each of

tutorialsarxiv-cs-ai

FourierQK: Filter Shape, Admissibility and the Leakage-Coverage Law

arXiv:2610.00009v1 Announce Type: new Abstract: Frequency-collapse attention [Zeris, 2026e] achieves large gains over standard dot-product attention by replacing the Q/K dot product with a bandpass-fi

Fractional Laplace Neural Operators: Exact Architectures, an Expressivity Frontier at Criticality, and Certified Stability for Memory-Driven Network Dynamics

arXiv:2610.00515v1 Announce Type: cross Abstract: Neural operators learn maps between function spaces, while hereditary network dynamics are described by Volterra resolvents with non-rational Laplace

From Discovery to Decision: Finite-Budget Recoverability in LLM Voting

arXiv:2610.01014v1 Announce Type: new Abstract: Voting over multiple LLM responses is a common primitive in test-time scaling and ensemble inference. Collecting more responses can expand the candidate

From Gradients to Capabilities: Understanding Multi-Teacher On-Policy Distillation

arXiv:2610.02179v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) aims to combine the strengths of RL-trained teachers in a single student, but how teacher signals affect par

From Image Latent Space to Fuzzy Rules: Interpretable Analysis of Gastrointestinal Foundation Model

arXiv:2610.00414v1 Announce Type: new Abstract: Foundation models pretrained on large-scale datasets demonstrate strong transferability to medical imaging tasks. However, understanding how their laten

safetyarxiv-cs-cv

From Isolated Feature to Orbits: Discovering Music Concepts via Multi-SAE Alignment

arXiv:2610.01864v1 Announce Type: cross Abstract: How can we understand what a music foundation model has learned extit{internally}? Most interpretability approaches, such as probing and Sparse Autoen

From Knowledge Access to Source Learning: Developing Source-Specific Competence

arXiv:2610.02150v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods i

From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures

arXiv:2610.01872v1 Announce Type: cross Abstract: While the literature on blockchain-assisted intrusion detection and prevention systems (IDS/IPS) for Internet of Things (IoT) and Industrial Internet

From Pixels to Policy: A Multi-Agent System for Intervention and Geo-Spatial Decision Support

arXiv:2610.01870v1 Announce Type: new Abstract: Urban environments are shaped by design choices with long-term implications for health, safety, and quality of life, yet evaluating proposed interventio

safetyarxiv-cs-cv

From Proposal to Verified Effect: Praxa, an Evidence-Bound Harness for Governed AI Agent Execution

arXiv:2610.00015v1 Announce Type: new Abstract: Large-language-model agents can propose and execute actions, but proposal, authority, dispatch, verified external effect, and serving promotion are diff

Agents

From Reasoning Failures to Composable Video Spatial Intelligence

arXiv:2610.01999v1 Announce Type: new Abstract: Spatial reasoning benchmarks evaluate vision-language models across diverse tasks, but task-level scores do not reveal which underlying capabilities acc

agentsarxiv-cs-cv

Tutorials

From Redundancy to Minimality: Fixed-Point-Guided Hierarchical Reduction of Learned Piecewise-Linear Dynamics

arXiv:2610.01369v1 Announce Type: new Abstract: Understanding a nonlinear dynamical system from time series requires not only reproducing its trajectories, but also identifying a simple representation

tutorialsarxiv-cs-lg

From Task Mixtures to Specialized Experts

arXiv:2610.00580v1 Announce Type: new Abstract: In collaborative foundation model fine-tuning, client data is rarely homogeneous. Instead, clients typically possess unknown mixtures of distinct data d

local-aiarxiv-cs-lg

Frozen Scenes, Shifting Winners: Configuration Fragility in Text-to-3D Evaluation

arXiv:2610.00447v1 Announce Type: new Abstract: Can a text-to-3D leaderboard change when every generated scene stays fixed? We audit this question for rendered-image evaluation, where camera settings

Fully Online Decentralized Learning in Stochastic Games with Unknown Independent Chains

arXiv:2610.01181v1 Announce Type: new Abstract: We consider stochastic games with independent controlled chains and unknown transition kernels, where players observe only their local states and realiz

Function-Structured Reinforcement Learning with Executable Verifiers for Mathematical Reasoning

arXiv:2610.01729v1 Announce Type: new Abstract: Algorithmic mathematical reasoning requires reliable decomposition, computation, and aggregation. Final-answer rewards provide limited guidance on inter

Fusing Visual and Textual Representations via Multi-layer Fusing Transformers for Vietnamese Visual Question Answering

arXiv:2610.01637v1 Announce Type: new Abstract: In recent decades, artificial intelligence has made significant progress in understanding and interacting with images. One of the important applications

applicationsarxiv-cs-cv

Fusion techniques of time frequency-based images to predict the outcome of rTMS depression therapy

arXiv:2610.00380v1 Announce Type: new Abstract: Depression is a mental condition that can lead to suicide and self-harm. Predicting the outcome of depression treatment is one of the most difficult tas

FutureWorlds: Learning Robotic World Models from Alternative Futures

arXiv:2610.01019v1 Announce Type: new Abstract: Robotic world models predict action-conditioned future scenes, providing a foundation for understanding action outcomes. However, turning alternative pr

safetyarxiv-cs-cv

G2-Nav: Grounded and Guarded Vision-Language Costmaps for Robot Social Navigation

arXiv:2607.16956v2 Announce Type: replace Abstract: Social navigation requires the robot to reason and respond in complex real-world environments. While recent works attempt to incorporate human-level

safetyarxiv-cs-ro

Gacha Decoding: Eliciting Diverse Generations Through Instruction Following

arXiv:2610.01382v1 Announce Type: new Abstract: We introduce Gacha Decoding, an inference-time method for eliciting diverse language model generations that scales with model capability. Across open-en

GenCOPE: Syn2Real Generalized Category-Level Object Pose Estimation for Robotic Picking

model-releasesarxiv-cs-cv

arXiv:2610.01758v1 Announce Type: new Abstract: Category-level object pose estimation (COPE), capable of generalizing to intra-class unknown objects, has become a core technique for robotic 3D scene u

Generalist Representation, Specialist Detection: TS-Router for Time-Series Anomaly Detection

arXiv:2610.00978v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of nor

applicationsarxiv-cs-ai

Generalization in Neural Networks Through the Lens of Magnitude Potential

arXiv:2610.01633v1 Announce Type: new Abstract: Explaining generalization and training dynamics in neural networks remains a challenge, and various approaches have been developed to study different as

Generalization Is Stability, Not Accuracy: Multi-Axis Evaluation of LLMs

model-releasesarxiv-cs-ai

arXiv:2610.01428v1 Announce Type: cross Abstract: Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed i

Generalized Biomedicine Discovery

arXiv:2610.00120v1 Announce Type: new Abstract: In real-world clinical practice, medical images face open-world shifts: (i) long-tailed rare diseases, (ii) subtle lesions dominated by normal anatomy,

Generalized Design Choices for Deepfake Detectors

model-releasesarxiv-cs-cv

arXiv:2511.21507v2 Announce Type: replace Abstract: The effectiveness of deepfake detection methods often depends less on their core design and more on implementation details such as data preprocessin

Generalized Engression Models

arXiv:2610.01823v1 Announce Type: cross Abstract: We consider estimating the conditional distribution of a multivariate outcome given covariates when its coordinates may be continuous, binary, categor

Generation Provenance Before Behavior Attribution: Auditing Synthetic Speech Research Objects

arXiv:2610.01378v1 Announce Type: new Abstract: Attributing model behavior to synthetic training data requires knowing what produced each training item before estimating what that item caused. A wavef

applicationsarxiv-cs-ai

Generative Cinematographer: Composing Camera and Object Motion in 3D

arXiv:2610.02180v1 Announce Type: cross Abstract: Current controllable video generation systems often rely on 2D motion trajectories or sparse drag signals for object motion. These controls are ambigu

Generative modeling of intrinsically disordered protein regions by reinforcing sparse autoencoder features

arXiv:2610.02189v1 Announce Type: new Abstract: Intrinsically disordered protein regions (IDRs) play central roles in cellular processes such as transcriptional regulation, signal transduction, and su

local-aiarxiv-cs-lg

Generative Modeling of Stochastic Dynamics for Long-Time Evolution

arXiv:2610.00546v1 Announce Type: cross Abstract: Exact stochastic equations for non-equilibrium dynamics are rarely accessible. We show that the long-time evolution of stochastic dynamics can be pred

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation

arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr

GeoLatent: Geometry-Guided Latent Structuring with Routed Optimization for 3D Reasoning

arXiv:2610.02091v1 Announce Type: cross Abstract: Despite progress in vision-language models, 3D spatial reasoning from 2D images remains challenging. Text-based methods describe intermediate geometry

Geometric Similarity in VLM Low-Level Vision Representations

arXiv:2610.00848v1 Announce Type: cross Abstract: Vision-language models (VLMs) have emerged as powerful candidates for universal vision backbones, with representative architectures including autoregr

Geometry-Aware Adaptation for Pretrained Models

arXiv:2307.12226v3 Announce Type: replace-cross Abstract: Machine learning models -- including prominent zero-shot models -- are often trained on datasets whose labels are only a small proportion of a