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MemEvo: Automatic Discovery of Streaming Video Memory Mechanisms

arXiv:2609.36581v1 Announce Type: new Abstract: Query-agnostic streaming video understanding requires vision-language models to continuously compress an indefinitely growing visual stream into a bound

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More Programs or More Rolls? Separating Coverage from Specialization in LLM Harnesses

DGX agent

arXiv:2609.35873v1 Announce Type: new Abstract: Automated generation of LLM harnesses promises to improve inference through task specialization. Yet additional answer coverage can arise from repeated

tutorialsarxiv-cs-ai

30 Sept 2026

Mubric: Mutation Testing-Guided Rubric Generation for LLM Evaluation

arXiv:2609.37322v1 Announce Type: new Abstract: Rubric-based evaluation is widely used to assess LLM-based systems by decomposing response quality into task-specific scoring criteria. However, automat

Multimodal Detection of Higher-Order Behavioral Constructs: Self-Compassion in Structured Reflective Interaction

arXiv:2609.37148v1 Announce Type: cross Abstract: Many of the qualities that matter most in how people learn and grow, how someone regulates their emotions, reflects on a setback, or stays aware of ot

Neural networks for spectral optimization

arXiv:2609.36047v1 Announce Type: cross Abstract: Given a functional dependent on the spectrum of a differential operator, we address the problem of finding a domain which optimizes this functional. P

NHO: A Neural Hamiltonian Operator for Anchor-based Region Localization and Dense Correspondance

arXiv:2609.37048v1 Announce Type: new Abstract: Non-rigid partial-to-full shape correspondence from sparse anchors requires identifying the corresponding region on the full surface and recovering dens

Non-negative Matrix Factorisation with Topological Regularisation

arXiv:2606.17531v2 Announce Type: replace Abstract: Non-negative matrix factorisation (NMF) learns additive representations from data, but non-negativity alone does not ensure interpretable basis func

On the spectral properties of generative denoiser Jacobians

arXiv:2609.36210v1 Announce Type: cross Abstract: Generative denoising models, such as diffusion and flow-matching, learn to sample from complex distributions by training a deep neural network denoise

OntoTKGE: Ontology-Enhanced Temporal Knowledge Graph Extrapolation

arXiv:2604.05468v3 Announce Type: replace Abstract: Temporal knowledge graph (TKG) extrapolation is an important task that aims to predict future facts through historical interaction information withi

Passive-Dynamic-Walking-Inspired Dynamics Guidance for Energy-Efficient Humanoid Locomotion

arXiv:2609.35935v1 Announce Type: new Abstract: Learning energy-efficient humanoid locomotion requires discovering mechanically economical gait coordination, not merely reducing actuator effort. Reinf

tutorialsarxiv-cs-ro

Persistence Forcing: Exploiting Feature Specialization in Pixel-Space Diffusion

arXiv:2609.36014v1 Announce Type: new Abstract: Pixel-space diffusion Transformers (DiTs) directly operate on high-dimensional visual data, yet their hidden representations typically undergo uniform r

Pretraining Latent Information Feedback Transformers with Teacher Supervision

arXiv:2609.38149v1 Announce Type: new Abstract: Transformer language models (LMs) are feed-forward: deep-layer representations are never fed back to shallower layers, and the only pathway for informat

PreviewDiff: Multimodal Critic-Guided Search over Diffusion Latents

arXiv:2609.36199v1 Announce Type: cross Abstract: Diffusion models can produce striking images and videos, but they still struggle with the compositional details that make a generation faithful to a p

Pure and physics-guided deep learning approaches for spatio-temporal groundwater level prediction

arXiv:2603.25779v2 Announce Type: replace-cross Abstract: Groundwater represents a key element of the water cycle, yet it exhibits complex and context-dependent relationships that make its modeling ch

Query claims in natural language with Amazon Bedrock Knowledge Bases

This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon

tutorialsaws-ml-blog

RED: Reconstruction Evolution Dynamics for Generalizable AI-Generated Image Detection

arXiv:2609.36822v1 Announce Type: new Abstract: The rapid evolution of image generators calls for forensic cues that generalize beyond known generation mechanisms. Existing detectors often rely on sta

Reimagine Video Dynamics

arXiv:2609.36496v1 Announce Type: new Abstract: Most video editing methods focus on changing the appearance of the source video, while offering limited control over its dynamics. We introduce Reimagin

Rethinking Reasoning Paths as Phase-Structured Trajectories

arXiv:2609.36461v1 Announce Type: new Abstract: Large language models often improve problem-solving performance by generating multi-step reasoning paths, yet how to analyze the hidden states along the

Reverberation: Learning the Latencies Before Forecasting Trajectories

arXiv:2511.11164v3 Announce Type: replace Abstract: Bridging the past to the future, connecting agents both spatially and temporally, lies at the core of the trajectory prediction task. Despite great

ReWorld-Track: A Recursive Event World Model for Language-Guided Multi-Camera Tracking

arXiv:2609.36677v1 Announce Type: new Abstract: Language-guided multi-camera tracking must preserve a target identity across unobserved gaps, where similar candidates and uncertain returns can make ea

Riemannian Splat Regression Models for Learning Time Fields on Arbitrary Riemannian Manifolds

arXiv:2609.36561v1 Announce Type: new Abstract: Motion planning on arbitrary Riemannian manifolds is an important and difficult problem that frustrates typical planning methods for Euclidean spaces. I

tutorialsarxiv-cs-ro

S2T-Unet: A Structure-to-Style Framework for Inter-Modality MRI Translation

arXiv:2609.36866v1 Announce Type: new Abstract: Inter-modality MRI translation aims to synthesize missing MRI modalities from available acquisitions, reducing the need for additional scanning while pr

Scaling Full Conformal Image Classifiers

arXiv:2609.37298v1 Announce Type: cross Abstract: Conformal prediction provides set-valued predictions with distribution-free coverage guarantees, making it attractive for high-stakes image classifica

Scaling Influence Functions in LLMs through Eigenbasis-Corrected One-Bit Gradient Projection

arXiv:2609.37842v1 Announce Type: cross Abstract: Influence functions estimate how individual training examples affect the behavior of large language models (LLMs). Analyzing how training data influen

Seeing Time: Visual-Temporal Representation Learning for Interpretable Time Series Clustering

arXiv:2609.36873v1 Announce Type: new Abstract: Multivariate Time Series (MTS) clustering is an important tool in temporal data mining, aiming to discover latent group structures from complex observat

Sieve and Sage: Efficient Distraction Filtering for Reliable RALM Abstention

arXiv:2609.35794v1 Announce Type: new Abstract: Just as Socrates recognized the limits of his own knowledge, Retrieval-Augmented Language Models (RALMs) should learn to abstain when the retrieved evid

Small teams are taking on more with AI—from finding customers to building products and managing finances. Our new report explores how small …

Small teams are taking on more with AI—from finding customers to building products and managing finances. Our new report explores how small businesses are putting AI agents to work. And through a new

tutorialsopenai--x

SYNCR: Diagnosing and Learning Cross-Video Reasoning from Simulation

arXiv:2609.37918v1 Announce Type: new Abstract: Reasoning across videos requires aligning events, matching identities, comparing motion, and integrating partial observations. Evaluating these capabili

TAEC: Trajectory-Aware Evidence Coordination for Multi-Step Visual RAG

arXiv:2609.37349v1 Announce Type: cross Abstract: Multi-step visual retrieval-augmented generation (RAG) answers complex questions by repeatedly retrieving visual evidence, updating an intermediate st

Targeted Visual Counterfactual Explanations for Contrastive Vision-Language Model

arXiv:2609.37638v1 Announce Type: new Abstract: Current explanation methods for contrastive vision--language models such as CLIP mainly identify important regions without showing how to change the inp

Task-Relevant Null-Space Residuals for Non-Injective Neural Mappings

arXiv:2609.37272v1 Announce Type: new Abstract: Non-injective mappings in neural networks map distinct inputs to the same representation, thereby implicitly inducing equivalence relations in the input

The Uneven Decline of Collective Knowledge Production: Evidence from Stack Overflow After Generative AI

arXiv:2609.36069v1 Announce Type: cross Abstract: Generative AI (Gen AI) is reshaping how individuals learn and work, but its consequences for collective knowledge, the shared body of knowledge that o

Think Before You Restore: Risk-Aware Manchu Manuscript Restoration with Stroke-Guided Attention

arXiv:2609.36243v1 Announce Type: cross Abstract: Full-page blind restoration of historical Manchu manuscripts is challenging due to scarce annotations, unknown degradation regions, and fragile connec

Thinking in Depth, Speaking Directly: Recurrent Latent Reasoning for Paralinguistically Grounded Spoken Dialogue

arXiv:2609.37818v1 Announce Type: cross Abstract: Empathetic spoken dialogue requires models to use both what is said and how it is said to decide how to respond. Explicit CoT can improve paralinguist

UNBIND: UNlearning By INference-time Directional Steering for Code LLMs

arXiv:2609.35913v1 Announce Type: cross Abstract: Code large language models acquire programming capabilities from large code corpora, but can also memorize implementations that later require removal.

When Trees Are Not Enough: Learning Mixed-Topology Feature Graphs with Adaptive Graph Sparse Autoencoders

arXiv:2609.36294v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) expose interpretable features in large language model activations, yet existing structured SAEs impose single-parent trees

Where Does Randomness Matter in Neural Cellular Automata?

arXiv:2609.36797v1 Announce Type: new Abstract: Stochastic cell updates are often used throughout the life of a neural cellular automaton (NCA), from backpropagation through time to final rollout. Thi

Why Cross-Skeleton Retargeting Is Non-Identifiable: Structural Limits of Generative Motion Models

arXiv:2609.37297v1 Announce Type: new Abstract: Cross-skeleton motion generation trains generative models to carry action structure and motion intention from one body to another. Yet a target motion t

Width Expansion as a Method for Class Incremental Learning

arXiv:2609.37702v1 Announce Type: cross Abstract: Class Incremental Learning (Class-IL) requires models to learn new classes over time while preserving previously acquired knowledge without access to

Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking

arXiv:2609.35021v1 Announce Type: new Abstract: Spatiotemporal prediction aims to learn discriminative representations from correlated temporal signals over spatial structures for accurate future infe

Age of Learning: Temporal Persistence of Prediction Errors as a Learning Signal

arXiv:2609.32593v1 Announce Type: new Abstract: Current machine learning algorithms primarily rely on instantaneous signals such as loss, margin, and prediction confidence to characterize model behavi

AnchorMixGAN: Anchor-Aligned Generative Semi-Supervision for DDoS Detection in Cloud-Integrated IoT Networks

arXiv:2609.32764v1 Announce Type: new Abstract: Detecting distributed denial-of-service (DDoS) attacks in cloud-integrated IoT networks is difficult when labeled traffic is scarce. Generative semi-sup

Arithmetic Simplicity in Stochastic Gradient Methods

arXiv:2609.32240v1 Announce Type: new Abstract: A gradient descent method is arithmetically simple if the operations are limited to +,-, imes, and division x/2^t with integer t. An arthmetically simpl

Augmenting Visual Anomaly Detection with Automated Interpretability

arXiv:2609.33818v1 Announce Type: new Abstract: Visual anomaly detectors identify deviations from known-normal data, but their anomaly signals may mix evidence of actual anomalies with benign visual v

Beyond the Manifold Hypothesis: Hybrid Spectral Parameterizations for Flow Matching

arXiv:2609.32432v1 Announce Type: new Abstract: Flow matching and diffusion can be trained to predict different quantities, most commonly the data x_1, the source noise x_0, or the velocity~v. Althoug

Beyond the Training Horizon: Mechanisms and Limits of Length Generalization in Looped Transformers

arXiv:2609.33144v1 Announce Type: new Abstract: Looped Transformers can generalize to reasoning chains longer than those encountered during training, but the computations enabling this behavior and li

CasEm: A Cascade Architecture for Long-Horizon Neural Emulation

arXiv:2609.34246v1 Announce Type: new Abstract: Autoregressive neural emulators can drift or diverge over long rollouts despite accurate short-term predictions. We introduce Cascaded Emulation (CasEm)

CAT: Can Trust be Predicted with Context-Awareness in Dynamic Heterogeneous Networks?

arXiv:2512.11352v2 Announce Type: replace Abstract: Trust prediction provides valuable support for decision-making, risk mitigation, and system security enhancement. Recently, Graph Neural Networks (G