Search: “inference”

Efficient Iterative Retrieval with Heterogeneous Batching

arXiv:2609.25405v1 Announce Type: cross Abstract: Modern information retrieval increasingly employs both embedding and generative models to handle complex queries. However, current serving systems suf

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EMERGE: Resolution-Agnostic Point Cloud Generation with Equivariant Graph-Based Diffusion

DGX agent

arXiv:2609.26039v1 Announce Type: cross Abstract: Point cloud generation has emerged as a crucial task for accurately capturing and reproducing the complexity of the physical world. However, existing

researcharxiv-cs-lg

23 Sept 2026

Entropy Can Flow, or It Can Guide. Be Entropy. LEDFlow: Introducing Entropy-guided Generation Order into Uniform Discrete Flow

arXiv:2609.25131v1 Announce Type: new Abstract: Uniform discrete flow permits repeated updates at every generation position. While continued revision supports correction of wrong tokens, it also expos

Error Bounds for Statistical Estimators in BTL Model with Parametric Multivariate Utility Functions

model-releasesarxiv-cs-lg

arXiv:2609.26326v1 Announce Type: cross Abstract: We study preference elicitation under the Bradley-Terry-Luce (BTL) model where the true partworth vector is unknown and has to be estimated as a param

FinInteract: Benchmarking Clarification and Intent Integration in Ambiguous Financial Question Answering

arXiv:2609.24002v1 Announce Type: new Abstract: Large language model agents increasingly answer financial questions by searching regulatory filings. Such questions are often deceptively under-specifie

FireWorldBench: Benchmarking Complex Physical World Intelligence through Coupled-Field Fire Dynamics

arXiv:2609.23064v1 Announce Type: new Abstract: Understanding the physical world requires more than object recognition, scene description, and short-term visual prediction, as real-world physical syst

ForeDrive: Foresight-Guided End-to-End Autonomous Driving with a Planning-Relevant Latent World Model

arXiv:2609.26299v2 Announce Type: new Abstract: Existing latent world models are typically optimized for future predictability, yet the resulting representations are not necessarily useful for plannin

safetyarxiv-cs-cv

Fysiverse-3D-Vision Technical Report: Generating Executable 3D Worlds from Images through Unified Spatial Reasoning

arXiv:2609.25741v1 Announce Type: new Abstract: Generative models have advanced image-conditioned 3D content creation, yet generating controllable and executable 3D scenes from a single image remains

safetyarxiv-cs-cv

Generalized Deep Regression for Repeated Measurements

arXiv:2609.25605v1 Announce Type: cross Abstract: In this paper, we study the estimation of a marginal regression function from independent units with repeated binary, count, or continuous responses u

GGUFs in transformers natively!

model-releasesr-localllama

Hey there folks! Aritra here from Hugging Face. I wanted to update you all about the latest changes in `transformers`. We now natively support GGUFs (llama cpp quants). You can use it like so: from tr

Graph Domain Adaptation Does Not End with Representation Learning

arXiv:2609.25692v1 Announce Type: new Abstract: Graph domain adaptation (GDA) transfers knowledge from a labeled source graph to an unlabeled target graph under shifts in both node attributes and grap

gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy

arXiv:2605.11269v2 Announce Type: replace-cross Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast wavef

HABILIS Brain 0: Geometry-Change Supervision for Vision-Language-Action and Residual Flow Recovery

arXiv:2609.25558v1 Announce Type: cross Abstract: Vision-language-action policies benefit from geometric supervision, but current-frame geometry alone does not explicitly describe the changes associat

safetyarxiv-cs-lg

Hapi: A Multivariable Land-Surface Transformer for Medium-Range Hydrological Forecasting at Continental Scale

arXiv:2609.22702v1 Announce Type: new Abstract: Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. Producing them at h

local-aiarxiv-cs-ai

High-Order Liquid Evidence Modeling for Continuous and Subtle GNSS Spoofing Detection in Autonomous Driving

arXiv:2609.26231v1 Announce Type: new Abstract: Continuous and subtle GNSS spoofing poses a serious threat to autonomous vehicles because forged positions may remain locally plausible while gradually

Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models

arXiv:2609.25927v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning

local-aiarxiv-cs-cl

Interweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models

arXiv:2609.25980v1 Announce Type: new Abstract: Probabilistic time series foundation models (TSFMs) provide coordinate-wise predictive distributions, but these marginals do not determine a joint distr

JAMPR+/L2D: scalable neural heuristic for constrained vehicle routing problems in dynamic environment

arXiv:2609.26275v1 Announce Type: new Abstract: The vehicle routing problems with real-world constraints (we consider vehicles capacity limits, time windows constrains, pickup-and-delivery multi-depo

applicationsarxiv-cs-lg

Jev isn't new tech. Its marketing targets people who think AI started with LLMs.

I keep seeing Jev presented as some new class of decision model, but most of what’s being advertised is just normal classifier behavior with modern zero-shot capabilities. It outputs probabilities ove

local-air-localllama

LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

safetyarxiv-cs-ai

Latest Exact Match Attention

arXiv:2609.25802v1 Announce Type: cross Abstract: We introduce latest exact match attention (LEMA), an attention variant for transformers where queries and keys are binarized and each query attends on

local-aiarxiv-cs-cl

Learning to Plan in Human-Robot Collaboration: Multimodal Reinforcement Learning for Adaptive Interaction

arXiv:2609.25274v1 Announce Type: new Abstract: Robot assistants for older adults and people with disabilities need to perform collaborative tasks with users effectively. The core component of these s

safetyarxiv-cs-ro

Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping

arXiv:2609.26325v1 Announce Type: cross Abstract: Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on acc

local-aiarxiv-cs-ro

MAGIC: Mixed-Granularity Agent Graphs via Incremental Construction with Dense-Reward Reinforcement Learning

arXiv:2609.26667v1 Announce Type: new Abstract: Collaboration topology shapes both the performance and execution cost of LLM-based multi-agent systems. Because tasks differ in complexity and required

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

arXiv:2609.26693v1 Announce Type: new Abstract: A coding agent must emit a valid tool call--a parseable invocation of a tool in the provided schema--before the harness can execute its chosen action. W

MECT: Mixture of Experts with CNN-Transformer Network for Speaker verification

arXiv:2609.24061v1 Announce Type: cross Abstract: In this paper, we propose MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone wi

researcharxiv-cs-ai

MemoryAthena: Adaptive Routing over Latent and Generated Memories

arXiv:2609.25853v1 Announce Type: new Abstract: Learned-memory methods store information in an explicit table and consume it through a separate reader, allowing addressing, storage, and reading to be

researcharxiv-cs-cl

MiMo-V2.6 (both Pro and Flash) is a benchmaxxed scam

model-releasesr-localllama

MiMo-V2.6-Pro has an insanely high score of 46 on AA, putting it at the head of the opensource models available. It also costs pennies. Flash is not out on AA yet, but it costs less than half on datac

MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale

arXiv:2609.25454v1 Announce Type: cross Abstract: Geographic measurements are often sparse, leaving large areas without labels for the quantities we want to map. Geographic implicit neural representat

MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

safetyarxiv-cs-cv

Modality-Gated Deep Adapters: Adding a Modality to a Frozen Embedding Model with Exact Preservation

arXiv:2609.26182v1 Announce Type: new Abstract: Multimodal embedding models are deployed at scale: retrieval indices, benchmark results, and behavioral audits all depend on the base model's exact outp

MotionForge: A Data Generation Pipeline and Large-Scale Benchmark for Long-Horizon Manipulation of Dynamic Objects with Domain Shifts

model-releasesarxiv-cs-ro

arXiv:2609.25689v1 Announce Type: new Abstract: Recent advances in learning-based robot policies have demonstrated promising progress, yet they are predom- inantly evaluated in static or quasi-static

MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis

arXiv:2410.14948v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their train

applicationsarxiv-cs-cl

On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Quality

arXiv:2609.26388v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in n

researcharxiv-cs-cl

Optimal Sequential Annotations for Off-Policy Evaluation

arXiv:2609.26707v1 Announce Type: cross Abstract: Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment

safetyarxiv-cs-lg

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th

PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices

arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

safetyarxiv-cs-cl

Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning

arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele

local-aiarxiv-cs-cv

Agents

Scale your own way, using HPA with built-in support for PromQL metrics queries in GKE

Earlier this year, we announced native support for Google Kubernetes Engine (GKE) custom metrics. This milestone allowed you to scrap external adapters and instead collect autoscaling metrics directly

agentsgoogle-cloud-ai

Agents

Self-Organizing Agent Teams Learn to Reason Together

arXiv:2609.22682v1 Announce Type: new Abstract: Collective intelligence depends not only on what team members know, but also on how they organize their work. When the structure of a solution is unknow

agentsarxiv-cs-ai

Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe

arXiv:2609.25728v1 Announce Type: new Abstract: Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural netwo

Skytopia: Monocular Drone Navigation with Action-Conditioned Latent World Models

arXiv:2609.26007v1 Announce Type: new Abstract: Monocular drone navigation requires reaching a goal in an unseen environment from a single forward-facing camera, which offers few cues for depth and sc

safetyarxiv-cs-ro

StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models

arXiv:2609.26071v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulat

applicationsarxiv-cs-ro

Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling

arXiv:2609.25657v1 Announce Type: new Abstract: We increasingly use machine learning to label scientific datasets. The models we develop and deploy are improving all the time, but they are not and wil

applicationsarxiv-cs-lg

Toolcompass: Guiding Tool Trialing, Not Suppressing It

arXiv:2609.25678v1 Announce Type: cross Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is tool trialing, i.e

Total Cost of Agency: Exact Attribution of Memory Injection Cost in Multi-Agent LLM Workflows

arXiv:2609.23790v1 Announce Type: new Abstract: Every node in a multi-agent large language model (LLM) workflow retrieves context from memory and injects it into its prompt, where those injected token