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From Pixels to Pairs: A Comprehensive Benchmark of LLM-Based Key-Value Extraction in Noisy Document Settings

arXiv:2609.17538v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for structured information extraction from documents, yet their behavior under realistic OCR noise re

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Research

Function Lives Where Variance Doesn't: Task-Weighted Charts of a Language Model's Computation

DGX agent

arXiv:2609.18989v1 Announce Type: new Abstract: How many dimensions does a language model's computation actually use? The question is ill-posed until one names a functional. Task-weighted charts make

researcharxiv-cs-ai

17 Sept 2026

Function-Preserving Data Generation for Zero-Shot Real-to-Sim-to-Real Manipulation

arXiv:2609.18293v1 Announce Type: new Abstract: Robotic data generation is a promising paradigm for scaling robot learning without collecting large-scale real-world data. However, generating geometric

safetyarxiv-cs-ro

FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing

model-releasesarxiv-cs-lg

arXiv:2512.22143v2 Announce Type: replace-cross Abstract: Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communicatio

G-Mamba: Sparse Graph-Guided Mamba for Audio-Visual Speech Enhancement

arXiv:2609.18009v1 Announce Type: cross Abstract: Lightweight audio-visual speech enhancement (AVSE) models face a critical trade-off between computational efficiency and cross-modal alignment accurac

safetyarxiv-cs-cl

Gated Residual Body-Hand Coordination for Whole-Body Humanoid Teleoperation

arXiv:2609.18763v1 Announce Type: new Abstract: Whole-body humanoid teleoperation commonly combines a motion-tracking policy with a separate dexterous-hand retargeter. However, independently generated

safetyarxiv-cs-ro

Gaze as Evidence for Common Grounding: A Cross-Corpus Analysis of MapTask and MUNDEX

arXiv:2609.18011v1 Announce Type: new Abstract: In collaborative tasks with asymmetric information, participants coordinate their understanding through interaction. We ask whether gaze provides eviden

researcharxiv-cs-cl

Local Ai

GazeDiT: Gaze-Accurate Diffusion Image Generation for Eye Tracking via Spatial Conditioning

arXiv:2609.17814v1 Announce Type: new Abstract: Diffusion models are increasingly used to generate synthetic training data, but precise label control remains difficult when the conditioning signal is

local-aiarxiv-cs-cv

Generalist-Specialist Mixture-of-Experts for Rare Pathology Detection in Multimodal Imaging

arXiv:2609.18688v1 Announce Type: cross Abstract: AI models for multimodal medical imaging must balance modality-specific specialization with cross-modal shared representations, a trade-off that pure

Generalizable Neural Reconstruction of High-Fidelity Surfaces via Sparse Volumetric Representations

arXiv:2507.05952v2 Announce Type: replace Abstract: Neural implicit representations have recently achieved impressive results in novel view synthesis and multi-view 3D reconstruction, yet both NeRF- a

researcharxiv-cs-cv

Generalizing Adam to Manifolds for Efficiently Training Transformers

arXiv:2305.16901v5 Announce Type: replace Abstract: One of the primary reasons behind the success of neural networks has been the emergence of an array of new, highly-successful optimizers, perhaps mo

researcharxiv-cs-lg

GenStream: Semantic Streaming Framework for Generative Reconstruction of Human-centric Media

arXiv:2609.18634v1 Announce Type: cross Abstract: Video streaming dominates global internet traffic, yet conventional pipelines remain inefficient for structured, human-centric content such as sports,

GeoCond: A Conditioning-Aware Reliability Adapter for Feed-Forward 3D Reconstruction

arXiv:2609.18465v1 Announce Type: new Abstract: Feed-forward 3D foundation models such as VGGT predict cameras, depth, and point maps in a single pass, but can fail silently under low overlap, low par

researcharxiv-cs-cv

GeoCueFormer: Geometry-Guided Wavelet Representation and Prediction-Cued Dual-Stage Decoder for Underwater Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.18069v1 Announce Type: new Abstract: Underwater semantic segmentation is essential for marine ecosystem monitoring, yet remains challenging due to severe visual degradation. Light absorptio

Geometric Shortcuts for Complex Trunk Postures: Dual-Helicity Coupling Enables Low-Dimensional Control

arXiv:2609.18050v1 Announce Type: new Abstract: How do elephant trunks generate complex postures without relying solely on fine segmental activation? We propose that part of this complexity arises fro

researcharxiv-cs-ro

Applications

Geometry beneath the Waves: Dense Priors for Sparse-View Underwater 3D Gaussian Splatting

arXiv:2609.18737v1 Announce Type: new Abstract: Underwater 3D reconstruction supports applications ranging from marine ecosystem monitoring and subsea inspection to underwater archaeology, education,

applicationsarxiv-cs-cv

Geometry-Driven Shadow Harmonisation for Composited Faces: A Multiplicative, Albedo-Preserving Relighting Pipeline

model-releasesarxiv-cs-cv

arXiv:2609.17740v1 Announce Type: new Abstract: Face swapping and face compositing pipelines routinely produce a face that is geometrically well aligned but photometrically implausible: the donor face

Gradient Descent with Stochastic Subspaces via Persistence of Memory

arXiv:2609.18416v1 Announce Type: cross Abstract: Stochastic subspace methods have gained popularity as gradient descent based techniques for large scale optimisation problems, especially in distribut

safetyarxiv-cs-lg

GrainSpeech: Less Context, More Detail for Compact Speech Synthesis

arXiv:2609.18856v1 Announce Type: cross Abstract: Compact acoustic models face a challenging quality-capacity trade-off. We investigate two factors in this regime: encoder context and Mel-spectrogram

GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

arXiv:2609.17695v1 Announce Type: new Abstract: A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence. GraphEcho tests whether agents mistake these

GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.18358v1 Announce Type: new Abstract: Robot manipulation policies often struggle to generalize beyond their demonstrations, even when new instructions involve familiar objects and behaviors.

Tutorials

GroundingVLN: Reasoning and Acting with Grounding for Vision-Language Navigation

arXiv:2609.18581v1 Announce Type: new Abstract: Although vision-language models (VLMs) possess strong visual understanding and reasoning capabilities, existing vision-and-language navigation (VLN) age

tutorialsarxiv-cs-ro

Hardware

GroupKV: Hierarchical KV Cache Management for Long-Context Diffusion LLM Inference

arXiv:2609.17573v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are emerging as a promising generative paradigm that complements autoregressive decoding. In long-context sett

hardwarearxiv-cs-lg

Local Ai

GVD: Governed Versioning and Deduplication for Document Repositories

arXiv:2609.17696v1 Announce Type: new Abstract: Document repositories evolve continuously. Guidelines and policies are revised, superseded, and re-uploaded, so the same content recurs in different wor

local-aiarxiv-cs-ai

GYROval: A Robust Benchmark for Cultural Value Orientation in Large Language Models

arXiv:2609.18384v1 Announce Type: cross Abstract: We present a robust benchmark for measuring cultural value orientation in large language models on the two Inglehart-Welzel axes over several domains

HALT: Hallucination Assessment via Log-probs as Time series

arXiv:2602.02888v2 Announce Type: replace-cross Abstract: Hallucinations remain a major obstacle for large language models (LLMs), especially in safety-critical domains. We present HALT (Hallucination

HAP: A Hand-Driven Active Perception Framework for Egocentric Head Motion Prediction

model-releasesarxiv-cs-ro

arXiv:2609.18548v1 Announce Type: cross Abstract: Egocentric motion forecasting has primarily focused on hands and manipulated objects, leaving future human head motion comparatively underexplored. Du

Hardware-Free Robotics Laboratories in Mixed Reality

arXiv:2609.18434v1 Announce Type: new Abstract: Teaching robotics relies on screen-based simulation, showing robot motion in an abstract coordinate frame rather than at real scale in the learner's own

safetyarxiv-cs-ro

HearInContext: A Benchmark for Implicit Context in Speech Recognition

arXiv:2609.18680v1 Announce Type: new Abstract: Contextual ASR can benefit from semantic cues or from target words explicitly provided in the context. We introduce HearInContext, a Mandarin--English b

Higher-order pruning of experts in mixture-of-experts language models

arXiv:2609.18916v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models suffer from large parameter counts, which create a significant memory bottleneck. Expert pruning is the most

HiLNO: A Hierarchical Latent Neural Operator with Multi-Scale Supervision for PDEs on General Geometries

model-releasesarxiv-cs-lg

arXiv:2609.18419v1 Announce Type: cross Abstract: Latent neural operators improve the efficiency of operator learning for partial differential equations (PDEs) by performing the main computation on co

Agents

HINT-Plan: Human Intention-Aware Robot Task Planning in Context-Rich Environments using Vision Language Models

arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often

agentsarxiv-cs-ai

How AI Assistants Respond to Repeated Abuse

arXiv:2609.17547v1 Announce Type: new Abstract: AI assistants are expected to remain useful during difficult interactions, but little is known about how repeated verbal abuse changes their engagement

How Calibration Content Shapes Attention-Based Reranking

arXiv:2609.17764v1 Announce Type: new Abstract: Attention-based rerankers score documents by aggregating query-to-document attention and subtracting a null-query calibration pass to remove positional

safetyarxiv-cs-cl

How Many Labels Does Model Choice Need? Certificates and Budgets for Selective Prediction

arXiv:2609.18622v1 Announce Type: new Abstract: Classifiers can make identical predictions yet require labels to compare their selective performance: confidence ranks weight the same errors differentl

safetyarxiv-cs-lg

How Model Growth, Recursion, and Boundary Operators Influence Scaling Exponents

arXiv:2609.19107v1 Announce Type: new Abstract: Scaling laws predict how loss decreases with increases in computation. We show, contrary to conventional wisdom, that architectural interventions can mo

researcharxiv-cs-lg

How Much is a Human Right Worth? ECtHR-NPD: A Benchmark for Predicting Non-Pecuniary Damage Awards

arXiv:2609.18908v1 Announce Type: new Abstract: Existing legal benchmarks cover diverse tasks, while continuous monetary remedies remain comparatively underexplored. We introduce ECtHR-NPD, to the bes

Tutorials

How to make effective use of domain experts for image classification?

arXiv:2609.17749v1 Announce Type: new Abstract: A lot of expectations have been put for years on integrating domain expert knowledge in image classification models. Several approaches have been explor

tutorialsarxiv-cs-cv

HPOQuest: A Rare-Disease Diagnostic Agent Using Active Phenotype Acquisition

arXiv:2609.18431v1 Announce Type: new Abstract: More than 300 million people worldwide are affected by one of over 7,000 known rare diseases, yet diagnosis remains difficult because patients initially

Human-Centric Grasp State Assessment: Toward Transferring Subjective Evaluation to Robots

arXiv:2609.17540v1 Announce Type: new Abstract: We propose a framework that transfers tacit human subjective criteria to robotic systems for the appropriate grasping of deformable objects. Achieving s

researcharxiv-cs-ro

Applications

Human Resilience in the AI Era -- What Machines Can't Replace

arXiv:2510.25218v2 Announce Type: replace-cross Abstract: AI is changing work and decision making faster than many institutions can adapt their operating practices. We argue that this adaptation gap m

applicationsarxiv-cs-ai

Hybrid coupling with numerics-informed neural networks and the overlapping Schwarz alternating method

arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using

researcharxiv-cs-lg

Hyperbolic Graph Representation Learning for Differential Diagnosis on Biomedical Knowledge Graphs

arXiv:2609.18481v1 Announce Type: new Abstract: Biomedical knowledge graphs combine ontology-derived hierarchies with transversal associations among heterogeneous entities such as phenotypes, diseases

Agents

Hypothesis-Driven Autonomous Materials Synthesis with Multimodal LLM Agents

arXiv:2609.18598v1 Announce Type: cross Abstract: Self-driving laboratories can explore synthesis conditions autonomously, but their decision-making layer is typically a black-box optimizer, and the o

agentsarxiv-cs-ai

Local Ai

HyQuant: Hybrid-Precision Quantization for LLM Attention

arXiv:2608.27875v3 Announce Type: replace Abstract: Quantization has been widely adopted in LLM training and inference to reduce cost and improve efficiency. However, low-bit quantization of the atten

local-aiarxiv-cs-ai

I code or AI code: A comparative evaluation of AI-rated scores in classroom observations

arXiv:2609.18274v1 Announce Type: cross Abstract: Classroom observations are widely recognized as a key tool for establishing benchmarks of education quality and guiding pedagogical improvement, yet t

'If I Had to Buy Just ONE: Galaxy S26 Ultra': Auditing AI-Generated Product Recommendations

arXiv:2609.18729v1 Announce Type: cross Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this

iMINDBench: iEEG Multi-Institution Neural Decoding Benchmark

model-releasesarxiv-cs-lg

arXiv:2609.18104v1 Announce Type: new Abstract: Intracranial electroencephalography (iEEG) is widely used to record electrical activity directly from electrodes inside the human brain, making it an at