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Grab a Coffee: Future-Aware Guidance for Discrete Diffusion with Compiled Objectives

arXiv:2609.35924v1 Announce Type: new Abstract: Discrete diffusion models generate sequences by iteratively resolving multiple tokens in parallel, offering a flexible alternative to left-to-right gene

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Graph-Conditioned On-Policy Agent Distillation from Off-the-Shelf Teachers

DGX agent

arXiv:2609.37522v1 Announce Type: new Abstract: On-policy distillation (OPD) trains compact language agents with teacher feedback on student-generated trajectories. In multi-turn tasks, compounding er

safetyarxiv-cs-lg

30 Sept 2026

Graph neural networks for sampling-invariant embeddings of organized signal sets

arXiv:2609.35934v1 Announce Type: cross Abstract: Sensor networks and radars can deliver signals as organized sets, e.g. ordered signals, signals describing range cells within a grid or signals percei

Graph-Spectral Flow Matching for Multivariate Time Series Anomaly Detection

arXiv:2609.36765v1 Announce Type: new Abstract: Multivariate time series anomaly detection typically relies on evaluating discrepancies between observations and outputs produced by models trained on n

GraphVQ: Structure-Aware Autoregressive Decoding over Context-Quantized Graph Tokens

arXiv:2609.37604v1 Announce Type: new Abstract: Graph foundation models need a discrete token representation, but casting a graph as a generatable token sequence faces a structural obstacle: edges spa

GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling

arXiv:2609.37934v1 Announce Type: new Abstract: Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured variab

Grounded Revision vs. Prior Injection: Probing Retrieval-Augmented Patent Claim Amendment

model-releasesarxiv-cs-cl

arXiv:2609.36550v1 Announce Type: new Abstract: Retrieval-augmented generation is widely used in professional writing, yet whether retrieval grounds revision or merely injects templates is rarely test

Group-Marginalized Self-Rewarding RL Drives Zero-Label Self-Evolving

arXiv:2609.36750v1 Announce Type: cross Abstract: Self-rewarding reinforcement learning (RL) enables large language models (LLMs) to self-evolve without human labels. Existing ensemble-based methods c

Local Ai

Guard Models Are Overconfident Where Base Models Are Uncertain

arXiv:2609.36477v1 Announce Type: cross Abstract: Guard models are used as safety classifiers, with confidence scores driving downstream moderation decisions. We evaluate five guard models for prompt

local-aiarxiv-cs-ai

Guide, Then Let Go: Gap-Adaptive Teacher Scheduling for Sparse-Reward Agentic RL

arXiv:2609.37898v1 Announce Type: new Abstract: Reinforcement learning for long-horizon agents typically relies on sparse outcome-based rewards. This leads to a severe cold-start problem, as early-sta

GUITAR: Structured Failure Diagnosis of GUI Agents via State Transitions

arXiv:2609.34113v2 Announce Type: replace Abstract: Understanding where and why Graphical User Interface (GUI) agents fail is essential for building more reliable systems, yet current evaluation relie

HACo: Learning Haptic Active Compliance for Force-Aware Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.36596v1 Announce Type: new Abstract: Contact-rich dexterous manipulation requires policies that translate physical feedback into motion commands while regulating interaction loads across ev

HandAnthro: Automated Hand Anthropometry from a Single Image

arXiv:2609.37855v1 Announce Type: cross Abstract: Hand anthropometry supports protective-glove design, but existing measurement methods often require trained operators, specialized hardware, or manual

Agents

HaPRL: Human-Anchored Process Reinforcement Learning for Visual Search Agent

arXiv:2609.37190v1 Announce Type: new Abstract: Multi-turn visual search agents answer questions about high-resolution images by iteratively deciding where to look. Reinforcement learning for these ag

agentsarxiv-cs-cv

Hardware

Hardware-Aware Functional Kolmogorov-Arnold Networks for Efficient Medical Image Enhancement and Segmentation

arXiv:2609.36134v1 Announce Type: new Abstract: Functional Kolmogorov-Arnold Networks (FunKAN) achieve state-of-the-art accuracy on MRI Gibbs artifact removal and anatomical segmentation, but their 11

hardwarearxiv-cs-cv

Local Ai

HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment

arXiv:2609.38006v1 Announce Type: new Abstract: Running a language model locally offers advantages in privacy, latency, and cost, but local hardware fits only small models, which are less capable than

local-aiarxiv-cs-ai

HARMONI: Aligning Human and Scene Priors for Multi-View 4D Reconstruction

arXiv:2603.12789v3 Announce Type: replace Abstract: Recent advances in 3D foundation models have enabled joint reconstruction of humans and their surrounding environments. However, combining independe

researcharxiv-cs-cv

Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

arXiv:2609.36892v1 Announce Type: new Abstract: As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful

Applications

Harnessing Large Language Models to Compile Task-Relevant Context into Bayesian Optimisation

arXiv:2609.36788v1 Announce Type: new Abstract: Incorporating rich task-relevant context, such as domain knowledge and external observations, is a key capability yet remains challenging for Bayesian o

applicationsarxiv-cs-lg

HeadGuard: Selective Head Protection for Low-Bit VLM KV-Cache Quantization

model-releasesarxiv-cs-cv

arXiv:2609.35800v1 Announce Type: cross Abstract: Low-bit key-value (KV) cache quantization saves storage but can sharply degrade vision-language model (VLM) accuracy. We introduce HeadGuard, a compos

HEAR: Real Voices, Real Bias: A Large-Scale Human-Recorded, Demographically Diverse Benchmark for Audio Language Models

arXiv:2609.35952v1 Announce Type: cross Abstract: We introduce HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising 87k real huma

HEIR: Learning Human-Entity Interactions with Functional Roles

model-releasesarxiv-cs-cv

arXiv:2609.35955v1 Announce Type: new Abstract: Understanding human-entity interactions requires recovering each person-action event's participants, roles, and shared identities. This structure can su

Hardware

HelixWorld: A Real-time Interactive Audio-Visual World Model

arXiv:2609.38123v1 Announce Type: new Abstract: World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time. Yet prevailing interactive world models r

hardwarearxiv-cs-cv

HERO: Histology Encoder for Robust Representation in Oncology

model-releasesarxiv-cs-cv

arXiv:2609.35943v1 Announce Type: new Abstract: Foundation models trained on large pathology image corpora now provide strong, transferable representations for computational pathology. Over the past f

Agents

HeurEvo: Agentic Evolution of Hybrid Solver-Augmented Heuristics for Time-Critical Mathematical Optimization

arXiv:2609.36303v1 Announce Type: new Abstract: Recent advances in agentic heuristic design use AI agents and execution feedback to automate algorithm discovery for challenging optimization problems.

agentsarxiv-cs-cl

Hidden Reasoning Must Leak, but Need Not Be Readable: Fundamental Opportunities and Limits for Chain-of-Thought Monitoring

arXiv:2609.37312v1 Announce Type: cross Abstract: Can reasoning models trick chain of thought (CoT) monitors and perform hidden computation without revealing it in their thinking traces? We show that

Hierarchical Compression of Vision-Language Model Benchmarks

arXiv:2609.37515v1 Announce Type: cross Abstract: Thorough evaluation of vision-language models (VLMs) has become prohibitively expensive, as benchmarks span an ever-broader spectrum of capabilities a

Hierarchical Utility Calibration for Structured Multiclass Decisions

arXiv:2609.36532v1 Announce Type: cross Abstract: In multiclass probabilistic prediction, Utility Calibration (UC), which focuses auditing on specified utilities, has recently received attention as a

High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations

arXiv:2512.15684v2 Announce Type: replace-cross Abstract: Partial Least Squares (PLS) is a widely used method for data integration, designed to extract latent components shared across paired high-dime

safetyarxiv-cs-lg

High-Dimensional Simulation-Based Inference in Latent Spaces

model-releasesarxiv-cs-lg

arXiv:2609.37381v1 Announce Type: new Abstract: Neural simulation-based inference (SBI) has been widely successful in inferring a relatively small number of interpretable parameters from potentially h

High-Probability Convergence of Clipped SGD under Heavy-Tailed Noise and (L_0,L_1)-Smoothness

arXiv:2505.20817v3 Announce Type: replace-cross Abstract: Gradient clipping is widely used in language-model training to control heavy-tailed gradient noise and can improve convergence guarantees over

safetyarxiv-cs-lg

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

HiRAE: Hierarchical Representation Autoencoding with Residual Budgets

arXiv:2609.37775v1 Announce Type: cross Abstract: Pretrained visual representations support image generation, but may not fully preserve the fine-grained details needed for faithful reconstruction. Me

HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation

arXiv:2609.36559v1 Announce Type: cross Abstract: Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early

Homo-RAG: Homology-Guided Retrieval-Augmented Generation for Cross-Species Gene Function Prediction

arXiv:2608.25466v2 Announce Type: replace-cross Abstract: The functional annotation of genes in non-model organisms remains a significant challenge in computational biology, with 20-70% of sequenced g

Honeycomb: Constant-Size Scene Memory Representation for Video World Models

arXiv:2609.37690v1 Announce Type: new Abstract: Video world models require persistent scene memory to maintain consistency during long-horizon video generation. Existing spatial memory systems accumul

researcharxiv-cs-cv

Tutorials

HorizonFlow: Variable-Length Planning for Offline Goal-Conditioned RL

arXiv:2609.36896v1 Announce Type: new Abstract: Recent advances in generative planning have made trajectory inpainting a promising approach to offline goal-conditioned reinforcement learning. However,

tutorialsarxiv-cs-ai

How Can Recommendation Feedback Evolve Agent Memory?

arXiv:2609.37544v1 Announce Type: new Abstract: Content-generation agents continuously receive impressions, clicks, conversions, and negative feedback from recommendation systems, providing real-world

How Language Models Differ in Redistributing Attention-Head Activity Under Serial Demand

model-releasesarxiv-cs-lg

arXiv:2609.36221v1 Announce Type: new Abstract: The way a model distributes activity over each layer's attention heads offers a coarse view of how it routes information through depth; how this changes

How Local Mixing Encodes Relative Position in Global NoPE Attention

arXiv:2609.38109v1 Announce Type: cross Abstract: The attention operation is naively position invariant. However, positional information is fundamental to natural language, and therefore a variety of

How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification

model-releasesarxiv-cs-cl

arXiv:2609.37882v1 Announce Type: new Abstract: Every text classifier for an African language begins with a budgeting question: how many labelled examples are needed, and can labels from other African

How Medical VLMs Underutilize Their Vision Encoders: A Dermatology Perspective

arXiv:2609.36557v1 Announce Type: cross Abstract: Medical Vision-Language Models (VLMs) show significant promise for clinical image understanding, offering accurate diagnosis with interpretable reason

Applications

How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp

applicationsarxiv-cs-ai

How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats

arXiv:2609.35815v1 Announce Type: cross Abstract: Researchers across academia increasingly base significance claims on LLM judge scores and small-sample AI evaluations. Yet without well-calibrated con

Human-AI Collaboration: From Paradoxes to Patterns

arXiv:2609.36481v1 Announce Type: new Abstract: Evidence shows that humans and AI systems perform better together, by collaborating, than alone. This paper examines two key design dimensions of human-

Human-inspired, Task-Dimension-Guided Exploration for Efficient Learning in High Dimensions

arXiv:2609.36672v2 Announce Type: new Abstract: Efficient exploration in high-dimensional decision spaces remains a central challenge for decision-making systems. Humans, in contrast, can navigate lar

Hybrid Ensemble Learning for EEG-Based Epileptic Seizure Forecasting

arXiv:2609.35876v1 Announce Type: new Abstract: Epileptic seizure forecasting aims to provide actionable warnings before seizure onset, yet patient-independent generalization and false-alarm control r

Hybrid Feature Learning for Handwriting Verification

arXiv:1812.02621v2 Announce Type: replace Abstract: We propose an effective Hybrid Deep Learning (HDL) architecture for the task of determining the probability that a questioned handwritten word has b

researcharxiv-cs-cv