Search: “benchmark”

CAFE+FNO: Fourier Kernel Generation via Multiplicative Feature Composition

arXiv:2610.10105v1 Announce Type: new Abstract: The Fourier Neural Operator (FNO) learns solution operators of partial differential equations (PDEs) through Fourier-space kernel parameterization, but

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CAP: Codebook-Aligned Prediction for Tokenized Robot Policies

DGX agent

arXiv:2610.09178v1 Announce Type: new Abstract: Action tokenization converts continuous robot actions into discrete symbols that can be modeled autoregressively. However, existing tokenizer-based poli

safetyarxiv-cs-ro

8 Oct 2026

Certified by Abstention: Distribution-Free Guarantees for Chain-of-Thought Verifiers at Small Calibration Budgets

arXiv:2610.09541v1 Announce Type: cross Abstract: Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee. W

Child ASR Adaptation with Adult Retention: An Empirical Study

arXiv:2610.08827v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) systems often underperform for children and non-native speakers, while adapting adult ASR models to child speech can

researcharxiv-cs-cl

CIRRA: Dual-Level Continual Instruction Reconciliation with Ongoing Execution for Embodied Robot Agents in Interactive Household Tasks

arXiv:2610.08862v1 Announce Type: cross Abstract: Household robots must accommodate new user instructions while executing ongoing tasks. Existing agents often regenerate or extensively revise the rema

CMP-IRRT*: A Perception-Assisted Height-Adaptive Planner for Quadruped Robots

arXiv:2610.10470v1 Announce Type: new Abstract: Quadruped robots can traverse low obstacles, but many 2D planning pipelines still model obstacles as binary occupied regions and rely on sampling-based

safetyarxiv-cs-ro

Composing What Each Teacher Learned: Multi-Teacher On-Policy Distillation through Teacher-Relative Shifts

arXiv:2610.10460v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one

Continual Graph Multi-Agent Reinforcement Learning

arXiv:2610.10302v1 Announce Type: new Abstract: In Continual Multi-Agent Reinforcement Learning (CMARL), agents learn cooperative policies across sequences of tasks, aiming to adapt effectively to new

Correspondences as Decisions: JevNexus for Decision-Centric Schema Matching

arXiv:2610.09487v1 Announce Type: cross Abstract: Schema matching increasingly uses generative language models to rerank retrieved column candidates, although the underlying task is a bounded correspo

Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

arXiv:2610.10347v1 Announce Type: cross Abstract: Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically

Decoupling Exploration from Optimization in RLVR

arXiv:2610.10536v1 Announce Type: cross Abstract: Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints. A key promise of RLVR is t

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Tutorials

Depth-to-RGB: Repurposing a Frozen Depth Estimator for Geometry-Guided Compositing

arXiv:2610.09125v1 Announce Type: new Abstract: Reference-based object compositing inserts or replaces an object using a background image, a reference image, and a 2D compositing mask. These inputs gu

tutorialsarxiv-cs-cv

Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

arXiv:2610.09136v1 Announce Type: new Abstract: Learning a directed acyclic graph (DAG) from observational data is a challenging combinatorial problem due to the exponential growth in the number of ca

Tutorials

DisParQ: Self-Supervised Part Concepts for Interpretable Vision Foundation Models

arXiv:2610.09802v1 Announce Type: new Abstract: Concept-based vision models represent images through an intermediate layer of human-inspectable concepts, so what a model relies on can be traced to tho

tutorialsarxiv-cs-cv

Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs

arXiv:2610.10520v1 Announce Type: new Abstract: GNN-to-MLP distillation aims to retain the predictive accuracy of a message-passing teacher while deploying a graph-free MLP at inference. Existing meth

safetyarxiv-cs-lg

Do Vision-Language-Action Models Understand Instructions? A Mechanistic Interpretability Study on Language Grounding

model-releasesarxiv-cs-ro

arXiv:2610.10178v1 Announce Type: new Abstract: Vision-Language-Action models are designed to generalise across environments and task descriptions, raising the question of whether their action generat

Applications

Domain-informed Adaptive Sampling for Generalizable PINNs in Metal Additive Manufacturing via Conditional Flow Matching

arXiv:2610.09126v1 Announce Type: new Abstract: Accurate thermal modeling is essential in metal additive manufacturing (AM) for understanding the process-structure-property chain. Physics-informed neu

applicationsarxiv-cs-lg

DSTNet: Dynamic Spectral Trajectory Network for Causal Multi-Horizon Financial Forecasting

arXiv:2610.09654v1 Announce Type: new Abstract: Wavelet-based financial forecasters typically use the transform only to denoise, or reduce it to a single spectral snapshot at the forecast origin, and

Dual-QK: Sharp Queries and Flat Keys for Prunable 2-bit KV Caches

arXiv:2610.09827v1 Announce Type: new Abstract: Long inputs and extended generation increase the storage and access costs of the key-value (KV) cache. Low-bit quantization reduces storage and memory t

Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection

arXiv:2610.09993v1 Announce Type: new Abstract: Spatial defect signatures on wafer bin maps (WBMs) trace yield loss to specific process faults, yet supervised classifiers recognize only the defect typ

Environmental Change Detection for Real-World Change Analysis

arXiv:2506.11481v2 Announce Type: replace Abstract: Scene Change Detection (SCD) evaluates changes using predefined query-reference (i.e., present-past) image pairs. However, this formulation overlook

Executing Causal Structure Learning with Linear-Attention Transformers

arXiv:2610.10395v1 Announce Type: new Abstract: Transformers can execute algorithms on data given in their input. We ask whether they can do the same for causal discovery. We study a standard continuo

Local Ai

Explicit Geometric Chain-of-Thought for Vision-Language-Action in Autonomous Driving

arXiv:2610.10390v1 Announce Type: new Abstract: Vision-language-action~(VLA) models have emerged as a promising paradigm for autonomous driving. However, existing VLA models still suffer from a fundam

local-aiarxiv-cs-cv

Few-Shot Learning for Personalised Automated Pain Assessment

arXiv:2610.09692v1 Announce Type: new Abstract: Pain perception varies substantially across individuals, making it difficult for population-based classifiers to generalise across all subjects in a dat

From Global Alignment to Local Grounding: Zero-Shot Chinese Character Recognition with Radical Verification

arXiv:2610.09449v1 Announce Type: new Abstract: Zero-shot Chinese character recognition (ZS-CCR) aims to recognize characters whose categories are never observed during training, and typically relies

Gaussian Density Splatting Network

arXiv:2610.10396v1 Announce Type: new Abstract: This paper proposes a novel crowd counting approach, the Gaussian Density Splatting Network (GDSNet). Unlike methods that rely on conventional, grid-bas

researcharxiv-cs-cv

geodex: A Library for Motion Planning on Riemannian Manifolds

model-releasesarxiv-cs-ro

arXiv:2610.09165v1 Announce Type: new Abstract: Planning motions that respect the intrinsic geometry of a robot's configuration space, including its curvature and a configuration-dependent notion of c

GraphOPD: Graph-Augmented On-Policy Distillation for LLM Agents

arXiv:2610.08959v1 Announce Type: new Abstract: On-policy distillation post-trains large language model agents by supplying dense, step-level guidance from a teacher policy when the reinforcement-lear

HAN-Mamba: Hierarchical Selective State Space Networks for Multi-Scale Financial Volatility Forecasting

arXiv:2610.10323v1 Announce Type: new Abstract: Short-horizon realized volatility forecasting requires the integration of market information that evolves at incompatible temporal resolutions, from sec

HarnessIR: Harnessing Multimodal Foundation Models for Universal Real-World Image Restoration

arXiv:2610.10133v1 Announce Type: new Abstract: Real-world low-quality images suffer from complex mixed degradations, including but not limited to noise, blur, atmospheric effects, etc. Recent agentic

Tutorials

HCPN-GCN: Scaling Hierarchical Prototype Networks with Cone Geometry for Continual Graph Learning

arXiv:2610.08823v1 Announce Type: cross Abstract: Continual Graph Learning (CGL) aims to incrementally learn from graph-structured data while preserving knowledge acquired from previous tasks. A major

tutorialsarxiv-cs-cv

How Do LLMs Change Predictions Under Negation?

arXiv:2610.09571v1 Announce Type: new Abstract: Negation is an essential feature of human language, yet large language models (LLMs) remain unreliable in processing it. We evaluate recent open-source

HuMBLE: Human Motion-Driven Behavior Learning for Embodied Locomotion

arXiv:2610.10489v1 Announce Type: new Abstract: Despite recent advances in humanoid locomotion, controllers optimized for command tracking and robustness tend to produce mechanical gaits, whereas cont

safetyarxiv-cs-ro

I built a local server that speaks the Ollama API - sessions survive crashes, and your chat doesn't wait behind your agents

Disclosure first: I'm one of the maintainers, this is my project. If you've pointed Open WebUI or a script at a local server, you know the failure modes: the server restarts and every conversation is

model-releasesr-ollama

Identifiability of a dissipative knowledge-dynamics model: exact recovery under designed excitation, degeneration on observational data

arXiv:2610.09889v1 Announce Type: new Abstract: Human learning is a dissipative dynamical process: mastery accumulates through practice, decays through forgetting, and propagates across interdependent

InstanceBench: Diagnosing Referential Reasoning and Target Identity in Referring Expression Segmentation

arXiv:2610.09478v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) links natural-language descriptions to pixel-level object masks. Yet standard evaluation provides limited insigh

Inverting Multi-Vector Visual Document Indices

arXiv:2610.09920v1 Announce Type: cross Abstract: Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party.

It Is Not Seeing the Hazard: A Frozen Vision-Language Safety Score Measures Its Caption Bank

arXiv:2610.09517v1 Announce Type: new Abstract: Frozen vision-language models increasingly provide safety signals for reinforcement learning. Their use assumes that similarity to language describing d

safetyarxiv-cs-cv

Jevjitsu: Or, How We Tried Generalized Classifiers on Everything

Classification is one of the oldest problems in machine learning. Unlike modern decoding transformers, most classification models were non-autoregressive by nature. Before Jev, the common approaches w

model-releasesqdrant

jevman: AI decision models play Pac-Man

model-releasesr-localllama

The other week I posted about Jev vs. Kev compared and since then, OpenAI released the decisions endpoint, Cloudflare released Clef and many here asked about Laya as well. This time we compared six po

Judging in Latent Space: Efficient Generative Reward Modeling via Semantics-Preserving Compression

arXiv:2610.09788v1 Announce Type: new Abstract: Reward modeling often requires jointly representing and reasoning over multiple evaluation criteria, yet verbalizing this process token by token can inc

KGATE : a Knowledge Graph Embedding Training Environment

arXiv:2610.09927v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) models encode the entities and relations of a knowledge graph into a low-dimensional latent space, enabling tasks such a

Label-free cell counting and viability prediction with brightfield imaging and deep learning

arXiv:2610.10473v1 Announce Type: new Abstract: Cell viability assessment is a core requirement in cell culture systems, with critical applications in biopharmaceutical manufacturing and drug developm

LACE-CRAFT: Robot Co-Design with Actor Inheritance and Blackboard Collaboration

arXiv:2610.09283v1 Announce Type: new Abstract: Robot co-design couples morphology search with policy learning, yet training every new design from scratch discards acquired control experience. We pres

safetyarxiv-cs-ro

Learning in the Recurrent State: Gradient Descent with Linear Recurrent Networks

arXiv:2410.11687v4 Announce Type: replace Abstract: In-context learning lets a sequence model adapt to a new task from examples in its input. A prominent line of work shows how self-attention can be c

safetyarxiv-cs-lg

Learning Transition Kernels of Jump-Diffusion Processes with Conditional Diffusion Models

arXiv:2610.09045v1 Announce Type: cross Abstract: We study the problem of learning transition kernels for time-homogeneous jump-diffusion processes using conditional diffusion models, with the goal of

LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets

arXiv:2610.09872v1 Announce Type: cross Abstract: Evaluating agents by outcomes alone can obscure the capabilities that produce them. This problem is especially pronounced in evolving environments, wh

LoomSC: Scalable Deep Subspace Clustering with Projector Factorization and Exact Spectral Reduction

arXiv:2610.10266v1 Announce Type: new Abstract: Dense self-expression matrices and full-affinity spectral clustering limit the scalability of subspace clustering. We introduce the Latent Orthogonal Op

researcharxiv-cs-cv