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arXiv:2609.35497v1 Announce Type: new Abstract: Long video understanding relies on video memory to overcome the context limits of multimodal large language models. Existing methods follow a build-then

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Squeeze3D: Extreme Neural Compression with Latent Space Bridging

DGX agent

arXiv:2506.07932v2 Announce Type: replace-cross Abstract: We propose Squeeze3D, a novel framework that leverages implicit prior knowledge learnt by existing pre-trained encoders and decoders to compre

researcharxiv-cs-cv

29 Sept 2026

Stabilizing the Dynamic Low-Rank Training

arXiv:2609.32615v1 Announce Type: new Abstract: Training neural networks directly in a low-rank parameterization is an appealing route to reducing memory, compute, and storage simultaneously during bo

StoryEngine: A State-Grounded Agentic Framework for Video Storytelling

arXiv:2609.33627v1 Announce Type: new Abstract: Despite recent progress in agentic multi-shot video generation, producing coherent and consistent long-form stories remains challenging. Existing agenti

STRIDE: State-Transition Representation via Increment Dynamics and Evolution

arXiv:2609.32367v1 Announce Type: new Abstract: We introduce STRIDE (State-Transition Representation via Increment Dynamics and Evolution), which defines states through derivative fingerprints and lea

Structure-First Point Cloud Learning with Mapper Region Graphs

arXiv:2602.05522v2 Announce Type: replace Abstract: Robust 3D point cloud classification is often pursued by scaling up backbones or relying on specialized data augmentation. We instead ask whether st

SubRot: Signed Gradient Subspace Calibration for VLM Rotation Quantization

arXiv:2609.34884v1 Announce Type: new Abstract: Post-training quantization reduces the deployment cost of vision-language models (VLMs), but preserving multimodal capabilities at low bit widths remain

researcharxiv-cs-cv

SurgGMF: Fully Causal Gaussian Motion Forecasting for Anticipatory Surgical Scene Rendering

arXiv:2609.34733v1 Announce Type: new Abstract: Dynamic surgical scene modeling is essential for robotic perception, simulation, and decision support. Although existing neural rendering methods enable

researcharxiv-cs-cv

Surprising Success, Repeated Failure: Entropy-Guided Credit Assignment for Exploration in LLM Reasoning

arXiv:2609.33781v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) enhances reasoning in large language models (LLMs) through outcome-level feedback, yet recent appr

SV2V-RSim: A Comprehensive Benchmark for Self-Selective V2V Cooperative Perception with Near-Realistic Data

arXiv:2609.32863v1 Announce Type: new Abstract: Vehicle-to-Vehicle (V2V) cooperative perception enhances autonomous driving by enabling vehicles to share information beyond their direct line of sight.

SymbolicArena: A Unified Infrastructure for Benchmark Distillation and Dynamic Evaluation in Symbolic Regression

arXiv:2609.35113v1 Announce Type: new Abstract: Symbolic regression (SR) seeks concise and interpretable mathematical expressions from data for scientific equation discovery. Existing SR benchmarks fa

SynCo: Learning Cross-Modal Synergy by Contrasting Interaction Residuals

arXiv:2609.32846v1 Announce Type: new Abstract: Multimodal contrastive learning is a dominant paradigm for learning transferable representations from unlabeled data, but standard objectives primarily

Hardware

Systematic Exploration of Multi-core Architectures for Efficient LLM Serving using WaferAI-SIM

arXiv:2510.05632v2 Announce Type: replace-cross Abstract: With the widespread adoption of Large Language Models (LLMs), the demand for high-performance LLM inference services continues to grow. Multi-

hardwarearxiv-cs-lg

Hardware

TempoKV: Timely Staging of LLM KV Caches for Memory-Semantic Flash

arXiv:2609.35065v1 Announce Type: cross Abstract: Reusable prefix key-value (KV) caches can outgrow GPU memory in large language model (LLM) serving. A memory-semantic flash hierarchy offers SSD-backe

hardwarearxiv-cs-lg

Terminal-Register Certification for Finite-Measurement Learning of Multiscale Quantum States

arXiv:2609.33567v1 Announce Type: cross Abstract: Structured quantum-state learning not only depends on an expressive ansatz but also on an operational certificate that stays meaningful with finite me

Applications

Test-Time Generalized Category Discovery

arXiv:2609.33937v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) and Generalized Category Discovery (GCD) are traditionally treated as disjoint problems: the former adapts models to domain s

applicationsarxiv-cs-cv

The Exponentially Weighted Signature

arXiv:2603.19198v2 Announce Type: replace-cross Abstract: We introduce the exponentially weighted signature (EWS), a continuous-time model that computes iterated integrals of a path, where each increm

researcharxiv-cs-lg

Tutorials

The Geometry of Logic: Stratification Induces Semantic Structure and Robust Reasoning

arXiv:2609.32927v1 Announce Type: new Abstract: Transformer-based language models perform well on symbolic tasks, yet it remains unclear whether they learn generalizable rules or rely on statistical s

tutorialsarxiv-cs-lg

The Selection Rule Decides the Winner: A Pre-Registered Audit of Open-Set Graph Anomaly Detection

arXiv:2609.33370v1 Announce Type: new Abstract: Open-set graph anomaly detection trains on a few labeled anomalies from one class and must also find anomaly classes that were never labeled. Published

The Statistical Cost of Causal Discovery with Feedback

arXiv:2609.34050v1 Announce Type: cross Abstract: What determines the unavoidable sample cost of learning cyclic causal structure? For cyclic linear non-Gaussian models, we study exact condensation re

researcharxiv-cs-lg

The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond

arXiv:2609.33280v1 Announce Type: cross Abstract: Medical images are released with the reports that describe them, and protecting the image does not protect the report. This paper measures the text co

Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning

arXiv:2609.33715v1 Announce Type: new Abstract: Accurate numerical solutions of partial differential equations (PDEs) are crucial in numerous science and engineering applications. In this work, we int

Agents

TMCS: Tool-Grounded Multi-Agent Reasoning for Compositional Chemical Problem Solving

arXiv:2609.35336v1 Announce Type: cross Abstract: Despite the promise of Large Language Models (LLMs) in computational chemistry, rigorous combinatorial chemistry problems remain difficult because the

agentsarxiv-cs-cv

TNF based Spectral Embedding for Effective Application of Supervised Machine Learning Techniques in Automobile Insurance Fraud Detection

arXiv:2609.33376v1 Announce Type: cross Abstract: Fraud detection is an important area of research in the insurance business due to its financial implications. The primary aim of a fraud detection mod

researcharxiv-cs-cv

TokenCast: Forecasting Token Consumption During LLM Agent Execution

arXiv:2609.35760v1 Announce Type: new Abstract: When a large language model (LLM) agent executes the same task, token consumption can vary by over an order of magnitude across runs. The agent chooses

Topology-Adaptive Hyperbolic Graph Attention Networks Guided by the Hyperbolic Sombor Index

arXiv:2609.32275v1 Announce Type: new Abstract: Hyperbolic geometry has emerged as a principled space for representing hierarchical graphs. However, existing hyperbolic graph neural networks typically

Toward On-Chip Training of Spiking Neural Networks for Dense Event-Based Vision

arXiv:2609.32405v1 Announce Type: new Abstract: Event cameras provide low-latency, asynchronous visual sensing for resource-constrained robotics. Spiking neural networks (SNNs) process event streams n

Traceable Human-to-Humanoid Sign Language Benchmarking

model-releasesarxiv-cs-ro

arXiv:2609.33354v1 Announce Type: new Abstract: Sign data collection is costly, and teleoperation scales poorly, motivating reuse of large video corpora. Humanoid signing requires converting video-der

Two-Timescale Fine-tuning Provably Learns New Features for Two-Layer ReLU Networks

arXiv:2609.34667v1 Announce Type: cross Abstract: Fine-tuning pre-trained models on specialized tasks with scarce data is central to modern deep learning. Despite its empirical success, theoretical un

UMR: Universal Manipulation Representation

model-releasesarxiv-cs-ro

arXiv:2609.34256v1 Announce Type: new Abstract: General-purpose embodied manipulation hinges on a unified action representation that generalizes across embodiments and scales readily. Yet existing pol

Understanding the Subspace Stabilization of the Hessian and Gradient Covariance Matrix

arXiv:2609.31983v1 Announce Type: new Abstract: The phenomenon of the top subspace stabilization of the Hessian matrix is an surprising and critical aspect in study of the second-order information of

Uniform Race: Parameter-Free Approximate Rejection Sampling

arXiv:2609.34639v1 Announce Type: new Abstract: We study approximate sampling: given N independent samples from a proposal distribution mu, the goal is to select one whose distribution is close to a t

Universal Dynamic Portfolios

arXiv:2609.34643v1 Announce Type: new Abstract: Cover's Universal Portfolio (Cover, 1991) matches the performance of the best constant rebalanced portfolio in hindsight. We generalize this framework t

UNMATCH: Selective Unbalanced Token-Patch Matching for Forensic Image-Claim Verification

arXiv:2609.31766v1 Announce Type: new Abstract: Contextual image misuse pairs an image with a misleading claim. We study image-claim correspondence in fact-checked pairs containing out-of-context reus

Hardware

UnStep: Training-Free Acceleration of Causal Video Diffusion with Fewer Steps Than Distillation

arXiv:2609.32518v1 Announce Type: new Abstract: Distilling bidirectional multi-step video diffusion transformers into few-step causal models has become a common approach for streaming video generation

hardwarearxiv-cs-cv

Unsupervised spiking feature learning for event-based pedestrian crossing detection: approaching supervised accuracy without labelled training data

arXiv:2609.31671v1 Announce Type: new Abstract: Event cameras are well suited to pedestrian crossing detection, and spiking neural networks (SNNs) can process their output natively, but current SNN de

VastMAT: A Large-Scale Multi-Category Benchmark for Multi-Animal Tracking

arXiv:2609.34390v1 Announce Type: new Abstract: Multi-animal tracking (MAT) supports the study of animal movement, behavior, and group interactions. However, general multi-object tracking (MOT) benchm

Tutorials

VGGT-Diff: Visual Geometry Meets Diffusion for Sparse-View Novel View Synthesis

arXiv:2609.33253v1 Announce Type: new Abstract: We present VGGT-Diff, a geometry-routed multi-view diffusion model for sparse-view novel view synthesis. Existing novel view synthesis (NVS) methods fac

tutorialsarxiv-cs-cv

Agents

Vision-Language Agents for Active Perception in Optics Laboratories

arXiv:2609.32918v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experime

agentsarxiv-cs-cv

Local Ai

What Should Data Teach? Moving Bottlenecks Across Circuit, Store, and Use

arXiv:2609.32991v1 Announce Type: new Abstract: What should data teach a language model at a particular point in training? A circuit view reveals three distinct bottlenecks: forming a computation, mak

local-aiarxiv-cs-lg

What Should Federated LoRA Share? FedSAIL via Input-aware Subspace Alignment

arXiv:2609.32485v1 Announce Type: new Abstract: Federated low-rank adaptation (LoRA) requires identifying an update structure that is shared across heterogeneous clients. Prior work reports strong sim

What Should the Reflector See? An Empirical Study of Evidence in Reflective Prompt Optimization

arXiv:2609.32452v1 Announce Type: cross Abstract: Reflective prompt optimization revises instructions using examples of a model's behavior, but which evidence the reflector should receive remains uncl

What Visual Generators Need from Teachers: Rethinking Representation Alignment

arXiv:2609.34732v1 Announce Type: new Abstract: Representation alignment speeds up diffusion transformer training by pulling an intermediate block of the model (student) toward features of a frozen pr

safetyarxiv-cs-cv

When an Evaluation Rule Writes Training Labels: Measuring Human-Reference Forgiveness in NAVSIM

arXiv:2609.33189v1 Announce Type: cross Abstract: When the human reference scores zero on a metric, the released GTRS-Dense label generator for NAVSIM marks every candidate trajectory in the scene as

When the Score Becomes the Target: Rethinking Metric Validity in Autonomous Driving

arXiv:2609.34440v1 Announce Type: new Abstract: Driving benchmark scores are increasingly used not only for evaluation but also as optimization targets. This raises a fundamental question: do score ga

A Benchmark and Diagnostic Study of Epistemic Admission in Shared Agent Memory

model-releasesarxiv-cs-ai

arXiv:2609.30813v1 Announce Type: new Abstract: Evaluating claim admission in shared agent memory is challenging because repeated claims may be mistaken for independent evidence. An agent may copy or

28 Sept 2026

A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI Methods

arXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,

researcharxiv-cs-ai

28 Sept 2026

Local Ai

Adaptive Interaction Graphs for Particle Simulation