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Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

arXiv:2609.12994v1 Announce Type: new Abstract: Heavy-tailed empirical spectral densities of neural-network weight matrices are widely used as diagnostics of implicit self-regularization, but the step

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Research

Direct Topology Tracking in Continuous Implicit Models

DGX agent

arXiv:2609.12157v1 Announce Type: cross Abstract: We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representa

researcharxiv-cs-lg

14 Sept 2026

Hardware

Dissecting GPU Utilization for LLM Inference on Nvidia Hopper

arXiv:2609.12923v1 Announce Type: cross Abstract: A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The prob

hardwarearxiv-cs-lg

Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner

arXiv:2609.12651v1 Announce Type: new Abstract: While Reinforcement Learning from Human Feedback (RLHF) is the standard paradigm for aligning large language models with human preferences, its effectiv

Distributed Stochastic Optimal Control for Pattern-Oriented Swarms

arXiv:2609.12959v1 Announce Type: new Abstract: While offering significant promise for diverse applications, pattern-oriented swarms encounter multifaceted challenges in geometric control, self-organi

Agents

Diverse Minds, Divided Networks? Personality Composition, Polarization, and Collective Intelligence in LLM-Based Social Simulations

arXiv:2609.12444v1 Announce Type: cross Abstract: Simulated societies of large language model agents are used to study online polarization, and separately to study collective intelligence, but the two

agentsarxiv-cs-cl

Do LLMs Trust the Accuser or the Accusation? Measuring Belief Shifts in Werewolf

arXiv:2609.12446v1 Announce Type: cross Abstract: Social-deduction games such as Werewolf are increasingly used to evaluate LLM agents, but existing evaluations often rely on final game outcomes. We p

Doc2FRC: Length-Consistent Document-Level Machine Translation via Fixed-Range Chunking

arXiv:2609.12674v1 Announce Type: new Abstract: Advanced large language models (LLMs) with long context windows can substantially reduce input truncation in document-level machine translation (DocMT).

safetyarxiv-cs-cl

Does Video Memory Use What It Retrieves? A Causal Audit of Memory Specificity

arXiv:2609.12090v1 Announce Type: new Abstract: Video models increasingly use memory to preserve information over long sequences, with the assumption that gains come from retrieving and using the corr

researcharxiv-cs-cv

DRDN: Decoupled Representation Dynamic Network for From-Scratch ViT Class-Incremental Learning

arXiv:2607.01630v2 Announce Type: replace Abstract: Dynamic expansion methods for class-incremental learning (CIL) protect task-specific knowledge by growing dedicated tokens or subnetworks, yet our a

researcharxiv-cs-cv

Agents

Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyond

arXiv:2609.12660v1 Announce Type: new Abstract: This paper presents a Model Predictive Control-based motion planning and control pipeline for autonomous car racing capable of adapting to different dri

agentsarxiv-cs-ro

DropVLA: An Action-Level Backdoor Attack on Vision-Language-Action Models

arXiv:2510.10932v5 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models map multimodal perception and language instructions to executable robot actions, making them particularly

DRS-VPT: Directly Relocalizing in a Scan with Vision Point Transformers

arXiv:2609.12557v1 Announce Type: new Abstract: We present DRS-VPT, a feed-forward transformer architecture for foundational image-to-scan registration. Given query images and a reference 3D point clo

safetyarxiv-cs-cv

Hardware

Dual-guided Hierarchical Edge Localization for Large-scale Optimal Transport Across Dimensions

arXiv:2609.13010v1 Announce Type: new Abstract: Optimal transport (OT) compares distributions and aligns datasets in machine learning, yet unregularized discrete OT requires a linear program with quad

hardwarearxiv-cs-lg

Dual-Process Atomic Skill Learning: Decoupling Semantic Reasoning and Real-Time Control

arXiv:2607.10625v2 Announce Type: replace Abstract: Language-conditioned Imitation Learning (IL) is essential for enabling robots to perform complex tasks following natural language instructions. Howe

DuplexDrama: A Synthesized Dialogue Dataset with Scenarios, Full-Duplex Behaviors, Expressive Speech, and Sound Events

arXiv:2609.12872v1 Announce Type: new Abstract: We present DuplexDrama, the first synthesized spoken dialogue dataset that simultaneously covers four dimensions: (i) complete persona and scenario sett

Duplicating baseline benchmarks [D]

researchr-machinelearning

Suppose I create two machine learning models suppose tree and neural network for a task let's suppose regression problem, now suppose I am sending both of this paper to two different journals, now the

DWMP: Leveraging Dual World Models for Humanoid Obstacle Traversal

arXiv:2609.12347v1 Announce Type: new Abstract: Humanoid robots must traverse cluttered obstacle fields using onboard proprioceptive and visual observations, yet existing methods usually process multi

Hardware

Dynamic Expert Quantization for Scalable Mixture-of-Experts Inference

arXiv:2511.15015v4 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has become a practical architecture for scaling LLM capacity while keeping per-token compute modest, but deploying Mo

hardwarearxiv-cs-lg

Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model

arXiv:2609.13053v1 Announce Type: cross Abstract: Visual goal and dynamics prediction can provide language-conditioned robot policies with both a target outcome and a representation of action-dependen

Applications

DynSHAP: Towards Explainable Dynamic Survival Analysis

arXiv:2609.13042v1 Announce Type: new Abstract: Deep learning models for dynamic survival analysis (DSA) achieve strong predictive performance by incorporating longitudinal patient data, but their bla

applicationsarxiv-cs-lg

EAR: Entity-Aware Partitioning Approach for Retrieval-Augmented Generation Development

arXiv:2609.12268v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can improve knowledge-intensive question answering, but the first design choice is easy to overlook: how should the

Early Intervention for VFM-based Multimodal Medical Image Classification

arXiv:2603.17514v3 Announce Type: replace Abstract: Current methods for multimodal medical image classification (M3IC) face two major challenges. First, the prevailing 'fusion after unimodal image emb

Earth-Agent-Pro: Towards Real-World Full-Chain Earth Observation with Agents

arXiv:2609.12533v1 Announce Type: cross Abstract: Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare dat

Tutorials

Efficient AI Model Deployment Using Quantization Analysis Tool

arXiv:2609.11954v1 Announce Type: new Abstract: As deep learning models are increasingly deployed on resource constrained devices, the demand for efficient model optimization techniques continues to g

tutorialsarxiv-cs-lg

Efficient Vision-Language-Action Management and Serving for Robot Factories

arXiv:2609.12075v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models show high robotic manipulation capabilities via a two-stage design: a Vision-Language Model (VLM) stage followed b

EgoMaize: A First-Person Maize Instance Segmentation Benchmark under Severe Field Occlusion

arXiv:2609.12350v1 Announce Type: new Abstract: Close-range first-person field images are important for mobile maize phenotyping because many plant-level traits depend on in-canopy structures that are

Estimating Pedestrian Volumes from GIS-Derived Built-Environment Features: A Machine Learning Framework

arXiv:2609.12173v1 Announce Type: new Abstract: Transportation agencies need pedestrian volume estimates across entire road networks to prioritize safety investments, yet manual counts are expensive a

ESTS at WMT26: Routing-Informed Expert Pruning for Model Compression

arXiv:2609.12310v1 Announce Type: new Abstract: We describe six submissions under the team name ESTS to the unconstrained WMT26 Model Compression Shared Task for English--Simplified Chinese and Englis

EventMemAgent: Hierarchical Event-Centric Memory for Online Video Understanding with Adaptive Tool Use

arXiv:2602.15329v2 Announce Type: replace Abstract: Online video understanding requires models to perform continuous perception and long-range reasoning within potentially infinite visual streams. Its

Exact ReLU realization of binary affine refinement iterates via reflection folding and cone switching

arXiv:2609.11962v1 Announce Type: cross Abstract: We study vector-valued binary affine refinement operators with finitely supported matrix masks and compactly supported continuous piecewise linear inp

Expert-Space Exploration in MoE Reinforcement Learning

arXiv:2609.13058v1 Announce Type: new Abstract: Reinforcement learning (RL) has become central to post-training of large language models. Recent advances in RL for Mixture-of-Experts (MoE) models have

safetyarxiv-cs-cl

ExpertHTR: Unified Handwritten Text Recognition with Multi-Task Learning and Sparse Mixture-of-Experts

arXiv:2609.12705v1 Announce Type: new Abstract: Handwritten text recognition resources are often small and distributed across collections that differ in language, script, document structure, and annot

Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration

arXiv:2609.11995v1 Announce Type: new Abstract: Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains chall

Explaining Time Series Forecasting with Horizon-Resolved Attribution

arXiv:2609.12639v1 Announce Type: new Abstract: Recent advances in explaining time series (TS) models have produced methods that identify which past values a prediction depends on. However, most exist

Explanations-Driven Active Feature Acquisition for Algorithmic Recourse

arXiv:2609.12179v1 Announce Type: new Abstract: Algorithmic recourse methods typically assume that a predictive model has access to all features of an individual. In practice, decisions are often made

ext{GSF-}hi: Global Stereochemical Fields for Chiral Graph Transformers

arXiv:2609.12532v1 Announce Type: new Abstract: Enantiomers share atoms, bonds, and pairwise distances yet can behave differently in chiral environments, so molecular encoders must respect atom relabe

Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement

arXiv:2609.12107v1 Announce Type: new Abstract: Development and humanitarian organizations produce and support surveys, administrative registries, and other data resources to inform research, policy,

Fable solved the Cyphral Distich (a 370 year old cypher). Super cool way to use Claude https://www.vals.ai/blogs/fable-solves-cyphral-distic…

model-releasesboris-cherny--x

Boris Cherny announced on September 14, 2026 that the software *Fable* had cracked the 370‑year‑old Cyphral Distich cipher. The claim was posted via Vals AI’s platform and highlighted a demonstration

Fast and Faithful: Principled Conditional Flow Matching for Inverse Problems

arXiv:2609.12953v1 Announce Type: new Abstract: Flow matching approaches to imaging inverse problems commonly incorporate measurements in two ways. Conditioning-based approaches supply measurement-der

researcharxiv-cs-cv

Fast BIB simulation at a future Muon Collider with generative machine learning

arXiv:2609.12054v1 Announce Type: cross Abstract: Beam-induced background (BIB) from muon decay products will be an overwhelming and unavoidable background at a future Muon Collider. In order to devel

Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models

arXiv:2506.13061v4 Announce Type: replace Abstract: Diffusion probabilistic models generate samples by learning to reverse a noise-injection process that transforms data into noise. A key development

Feature Recovery for Object Understanding After Irreversible Fire Damage

arXiv:2609.12078v1 Announce Type: new Abstract: Objects in post-fire environments often undergo irreversible physical transformations that change their geometry, material state, and visual appearance.

Fed-Equilibrium Framework for Topological Pareto Control in Robust and Fair Clinical Federated Learning

arXiv:2609.11937v1 Announce Type: new Abstract: The deployment of Federated Learning (FL) in multi-center clinical networks faces the challenge of 'knowledge dominance,' where high-volume hubs natural

Fewer Words, Not Fewer Tokens: Measuring the Sanskrit Tokenization Penalty per Proposition

arXiv:2609.12960v1 Announce Type: new Abstract: Sanskrit fuses case, number, person and tense into word endings and chains clauses into compounds, so it is information-dense per word. Whether that den

researcharxiv-cs-cl

FINESSE: An Agent-Based Simulator and Benchmark Dataset for Multimodal Financial Event Sequences

arXiv:2609.11993v1 Announce Type: new Abstract: Machine learning research in financial services is limited by the scarcity of representative open-source datasets. Existing resources are often narrowly

Fixed State, Long Reach: What a Constant-Size Cache Buys Block Diffusion at Scale

arXiv:2609.11998v1 Announce Type: new Abstract: Diffusion language models decode tokens in parallel, but their bidirectional denoiser rules out the naive key--value (KV) cache behind fast autoregressi

Tutorials

FLOAT Drone: A Fully-actuated Coaxial Aerial Robot for Close-Proximity Operations

arXiv:2503.00785v2 Announce Type: replace Abstract: How to endow aerial robots with the ability to operate in close proximity remains an open problem. The core challenges lie in the propulsion system'

tutorialsarxiv-cs-ro