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From Core to Detail: Unsupervised Disentanglement with Entropy-Ordered Flows

arXiv:2602.06940v2 Announce Type: replace Abstract: The unsupervised discovery of features that are both semantically meaningful and stable across runs remains a central challenge in representation le

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From DNA Design to DNA Slimming: Auditable Agentic Discovery of a Deletion-Only Designer

DGX agent

arXiv:2609.40143v1 Announce Type: new Abstract: Compact regulatory DNA can free up space in vector payloads, reduce synthesis and assay burden, and expose which sequence features drive predicted activ

model-releasesarxiv-cs-lg

1 Oct 2026

From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.39566v1 Announce Type: new Abstract: Foundation models can serve as clinical agents through tool-use harnesses. However, conventional medical benchmarks assess reasoning over preselected ev

From Image Interpretation to Clinical Reasoning: Upstream Physician-Context-Aware Multimodal Learning with Causal Reinforcement Learning

arXiv:2609.38924v1 Announce Type: new Abstract: Major adverse cardiovascular events (MACE) remain the leading cause of mortality worldwide. Opportunistic screening using routinely acquired clinical da

safetyarxiv-cs-cv

From Imitation to Reward Discovery: On-Policy Warmup for Agentic RL

arXiv:2609.39436v1 Announce Type: cross Abstract: Reinforcement learning with a verifiable reward (RLVR) offers a scalable approach to training language-model agents, yet sparse outcome rewards can le

From Local Whole-Body VLA Behaviors to Scene-Scale Aerial Manipulation

arXiv:2609.39670v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable task-conditioned interaction, but extending them to scene-scale aerial manipulation remains challenging due t

safetyarxiv-cs-ro

From Modes to Memories: Characterizing the Scale-Space Dynamics of Diffusion Models

arXiv:2609.39648v1 Announce Type: cross Abstract: Diffusion models are typically viewed as stochastic processes that transform noise into data. We take a complementary perspective: a diffusion model d

Tutorials

From Search to Signal: Online Post-Training in Automatic Heuristic Design

arXiv:2609.39383v1 Announce Type: cross Abstract: Large language model (LLM)-based automatic heuristic design (AHD) iteratively proposes and refines heuristics, pairing design rationales with executab

tutorialsarxiv-cs-ai

Agents

From Solo to Social Learning: Characterizing Recursive Social Improvement in LLMs

arXiv:2609.38516v1 Announce Type: cross Abstract: Large language models (LLMs) can now improve themselves by revising the instructions they follow, and LLM agents are increasingly orchestrated to work

agentsarxiv-cs-ai

From Spectra to Joint Schedules in LLM Pre-training: 3+3(+2) Scaling-Law Regimes

arXiv:2609.40148v1 Announce Type: new Abstract: Power-law learning curves are often treated as fixed properties of a model and its data, although learning-rate and batch-size schedules can change the

applicationsarxiv-cs-lg

From Speech to Editable Concepts: Probing Emotion Recognition with Concept Bottleneck Models

arXiv:2609.39453v1 Announce Type: cross Abstract: Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent appr

From Tokens to Policy: Causal and Interpretable Heterogeneous Treatment Effects Identification

arXiv:2606.17010v2 Announce Type: replace Abstract: Heterogeneous Treatment Effect (HTE) identification is essential to explain the impact of an intervention and optimize our policies accordingly. Exi

safetyarxiv-cs-lg

From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye

arXiv:2609.40064v1 Announce Type: new Abstract: Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across co

applicationsarxiv-cs-cl

From Verification Failures to Reusable Guidance for Coding Agents

arXiv:2609.39022v1 Announce Type: cross Abstract: Coding agents need to establish that a program satisfies a specification and that the specification captures the requested behavior. We study how expe

From Wrecks to Wisdom: Recovering Crash Mechanics from Real-World Multi-View Photos

arXiv:2609.39486v1 Announce Type: new Abstract: Estimating accident mechanics from real-world crashes is important for vehicle-safety analysis, injury modeling, crash-severity prediction, and operatio

safetyarxiv-cs-cv

Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification

model-releasesarxiv-cs-cv

arXiv:2609.39492v1 Announce Type: new Abstract: Matching the same vehicle across front and rear cameras is difficult because the cameras do not share a view and the vehicle's appearance changes substa

FrontierGS: Progressive View-Space Frontier Expansion for Sparse 3D Gaussian Splatting

arXiv:2511.16030v3 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) enables efficient, high-fidelity novel view synthesis, yet its performance degrades severely under sparse-view supervis

researcharxiv-cs-cv

Local Ai

Function beyond Form: Functional Correspondence for Cross-Embodiment Dexterous Grasp Generation

arXiv:2609.39006v1 Announce Type: new Abstract: Cross-embodiment dexterous grasp generation remains challenging because robotic hands differ substantially in geometry, topology, and kinematics. Existi

local-aiarxiv-cs-ro

Function-Space Transformer with Adaptive Anchors

arXiv:2609.38348v1 Announce Type: new Abstract: Many forms of data, including physical fields, geometric shapes, and visual signals, are naturally described by functions over continuous domains but ar

Future Video Generation Better Aligns with the Human Visual Cortex than Observed Video

arXiv:2609.38819v1 Announce Type: cross Abstract: Studying the alignment between the internal representations of vision models and the responses of the visual cortex to the same observed visual stimul

Fyan: A Human--AI Harness with Semantic Auditing for Document-Level Formalization

arXiv:2609.39228v1 Announce Type: new Abstract: We present FYAN, a human--AI harness for document-level mathematical formalization. Rather than treating theorems in isolation, FYAN coordinates an end-

Game-Guided Skill Discovery through Self-Play for Playable Agent Control

arXiv:2609.40137v1 Announce Type: cross Abstract: We present Game-Guided Skill Discovery (GGSD), a framework that uses self-play in games to discover motor skills that are directly playable by humans.

GATE-ST: Gene-Aware Text-image Encoder for Spatial Transcriptomics

arXiv:2609.38690v1 Announce Type: new Abstract: Spatial transcriptomics enables spatially resolved gene expression analysis from slide-level images while preserving morphological features, providing v

GateSPINE: Gated Cross-View Fusion for Lumbar Spine MRI Report Generation

arXiv:2609.40091v1 Announce Type: cross Abstract: Automated report generation can ease the burden radiolo gists face when interpreting multi-sequence MRI studies. Unlike CT, MRI examinations comprise

Agents

GaugeVLM: Structuring Spatial Supervision with Measured Geometric Interventions

arXiv:2609.38285v1 Announce Type: cross Abstract: Vision-language models (VLMs) can contradict themselves across views of the same spatial relation and fail to respond when that relation changes. Addr

agentsarxiv-cs-ai

Gaussian Stippling: Efficient Sorting-Free 3D Gaussian Rendering through Hybrid Sampling and Spatiotemporal Reconstruction

arXiv:2609.38488v1 Announce Type: cross Abstract: Conventional 3D Gaussian Splatting (3DGS) requires depth sorting and ordered alpha blending to correctly render overlapping Gaussian primitives. Stoch

researcharxiv-cs-cv

GazeFlow: From Human Gaze Behavior to Generative Egocentric Gaze Prediction

arXiv:2609.38519v1 Announce Type: new Abstract: Egocentric gaze prediction enables many downstream applications but remains challenging, as human gaze is inherently stochastic. This stochasticity is c

researcharxiv-cs-cv

General Performance Guarantee for Human Torque Estimation-Based Task-Agnostic Assistive Exoskeleton Control

arXiv:2609.39558v1 Announce Type: cross Abstract: Accurate human torque estimation is crucial for enabling task-agnostic control in robotic exoskeleton systems. However, estimation errors may cause mi

Agents

Generalising from Self-Produced Data: Model Training Beyond Human Constraints

arXiv:2504.04711v2 Announce Type: replace Abstract: Current large language models (LLMs) are constrained by human-derived training data and limited by a single level of abstraction that impedes defini

agentsarxiv-cs-ai

Generalized Geometry Block Proximal Linearized Method for Multiblock Nonconvex and Nonsmooth Optimization

arXiv:2609.39301v1 Announce Type: cross Abstract: This paper considers a class of multiblock nonconvex and nonsmooth optimization problems arising in many applications. Existing methods construct prox

Local Ai

Generalized Residual Closure: General Learning Dynamics for Stability-Plasticity Compatibility

arXiv:2609.38911v1 Announce Type: new Abstract: Learning must acquire new capabilities while preserving both prior responsibilities and the capacity to learn again. We introduce Generalized Residual C

local-aiarxiv-cs-lg

Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot

arXiv:2511.11689v4 Announce Type: replace-cross Abstract: Generative AI chatbots built for mental health could extend access to care, but evidence from real-world use is limited. We report a single-ar

applicationsarxiv-cs-ai

Generative sequence modeling for infinite memory processes via predictive states

arXiv:2609.38524v1 Announce Type: cross Abstract: We consider estimating the one-step-ahead conditional distribution of a multivariate stochastic process. Many existing approaches rely on assumptions

GeoGAT: Bidirectional Temporal Sampling Meets Hierarchical Graph Attention for Global Video Geo-localization

model-releasesarxiv-cs-cv

arXiv:2609.39128v1 Announce Type: new Abstract: Global video geo-localization aims to infer the geographic location of a video worldwide, evaluating performance across four geographic hierarchies: cit

Geometry-physics confounding impairs PDE learning across varying domains

arXiv:2609.38623v1 Announce Type: new Abstract: Learning partial differential equation (PDE) dynamics across varying domains is central to predictive modelling and data-driven discovery of governing e

GeoNest: Learning to Select Failure-Aware Neighborhoods for the Irregular Knapsack Problem in a Circular Container

arXiv:2609.38863v1 Announce Type: cross Abstract: The two-dimensional irregular knapsack problem in a fixed circular container is an important combinatorial optimization problem for maximizing materia

GestAdapt: Workspace-Conditioned Co-Speech Gesture Generation for Humanoid Robots

arXiv:2609.38400v1 Announce Type: cross Abstract: Co-speech gestures for robots must adapt not only to speech and embodiment, but also to the workspace available for performing the motion. Since the s

Hardware

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

hardwarearxiv-cs-lg

GFD-OPD: Guidance-Folded On-Policy Distillation of Diffusion Models Across Scales

arXiv:2609.39692v1 Announce Type: cross Abstract: On-policy distillation (OPD) has demonstrated two important capabilities in language models: compressing large teachers into smaller students and merg

Ghost in the Encoder: Decodable Artist Identity Representations in Lyrics-to-Song Generation

arXiv:2609.39552v1 Announce Type: cross Abstract: Text-to-song generation models can be prompted to imitate specific artists or regurgitate entire songs from their training data. Although these phenom

applicationsarxiv-cs-lg

GLARE: Generating Listening Heads with Appropriate Reactions

arXiv:2609.40317v1 Announce Type: new Abstract: While talking head generation has advanced rapidly, generating natural listener behavior in dyadic conversations, which know when to react, how to react

safetyarxiv-cs-cv

Hardware

GPU-Accelerated Path-Dependent Marginal Information Gain for Autonomous Exploration

arXiv:2609.40297v1 Announce Type: new Abstract: Autonomous exploration demands that robots continuously evaluate candidate viewpoints based on their expected information gain and execution cost. Sampl

hardwarearxiv-cs-ro

GrammarRL: Effective Grammar-Constrained Decoding via Reinforcement Learning

arXiv:2609.39869v1 Announce Type: new Abstract: Grammar-constrained generation guarantees syntactic validity, but can substantially degrade semantic quality when the model's preferred outputs are poor

Graph Anomaly Detection as Finite-Horizon Control: Training-Free Scoring via Empirical Bayes

arXiv:2609.38424v1 Announce Type: new Abstract: Node-level graph anomaly detection (GAD) identifies nodes whose attributes and interactions deviate from dominant graph regularities. Existing GAD model

Graph Residual Conjugate Diffusion: SNR-Equalized Heat Flow for Graph Signals

arXiv:2609.39658v1 Announce Type: new Abstract: Diffusion models generate data by reversing a forward corruption process that typically approaches a simple Gaussian prior. Recent work has extended thi

GraphCert: Bootstrap Agentic Graph Reasoning with Certified Evidence Rubrics

arXiv:2609.38798v1 Announce Type: new Abstract: Graph agents extend large language models (LLMs) with the ability to actively explore and reason over knowledge graphs through multi-step interactions w

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

model-releasesarxiv-cs-cl

arXiv:2609.38923v1 Announce Type: new Abstract: Working agents need to read diverse files, coordinate tools, and produce deliverables. Training such agents requires tasks built on many real files with

GraphMAS: A Systematic Benchmark of Multi-Agent Coordination for Graph Learning

model-releasesarxiv-cs-lg

arXiv:2609.39777v1 Announce Type: new Abstract: LLM-based multi-agent systems coordinate specialized reasoning through aggregation, interaction, and adaptive control, yet their potential for graph lea