Search: “benchmark”

ARCS: Towards Precise Text-to-SQL via Structured Disambiguation

arXiv:2610.09396v1 Announce Type: new Abstract: As text-to-SQL systems move beyond demonstrations toward real-world deployment, ambiguity in user questions becomes a primary source of errors. Such amb

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Model Releases

AutoAdapt: Automatic Domain Discovery Enables Low-Cost Extensibility

DGX agent

arXiv:2610.10349v1 Announce Type: new Abstract: Instruction-tuned models are deployed into environments where domains are heterogeneous and evolve, yet adding new domains or data typically requires co

model-releasesarxiv-cs-lg

8 Oct 2026

BagDINO: Multi-View Baggage Re-Identification with DINOv3

arXiv:2610.10160v1 Announce Type: new Abstract: Mishandled checked baggage remains a recurrent issue in airport operations, and current recovery workflows still largely rely on tag-based tracking, whi

Agents

Beyond Outcome Rewards: Constructing and Assigning Retrieval Credit for Search Agents

arXiv:2610.10179v1 Announce Type: new Abstract: Search agents enable Large Language Models (LLMs) to iteratively retrieve and use information for complex multi-hop questions. Reinforcement Learning wi

agentsarxiv-cs-cl

Beyond Reconstruction: What Matters in Action Tokenization for Robot Policies?

arXiv:2610.09170v1 Announce Type: new Abstract: Autoregressive action-token policies such as vision-language-action models require action tokenizers to translate discrete token sequences into precise

Boundary-Free Contextual Biasing: Depth-Adaptive Gating and Reading-Space Matching for Unsegmented Languages

arXiv:2610.09467v1 Announce Type: cross Abstract: Contextual biasing supplies an ASR system with a list of expected words at inference time, but existing methods rely on word boundaries that Japanese

Bringing BNNs to Fast Event Processing

arXiv:2610.09873v1 Announce Type: new Abstract: Binary Neural Networks (BNNs) enable efficient deep learning deployment on resource constrained devices with weights and activations compressed to one b

researcharxiv-cs-cv

Agents

CADReasoner: Iterative Program Editing for CAD Reverse Engineering

arXiv:2603.29847v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) powers modern engineering, yet producing high-quality parts still demands substantial expert effort. Many AI syste

agentsarxiv-cs-cv

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

CAP: Codebook-Aligned Prediction for Tokenized Robot Policies

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

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

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

safetyarxiv-cs-cl

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

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

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