Search: “benchmark”

arXiv:2609.06208v1 Announce Type: new Abstract: Understanding human attention is fundamental for scene interpretation, yet existing approaches often rely on heavily trained models that lack interpreta

agentsarxiv-cs-cv

Agents

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From Narrative to Auditable Forecasts: A Structured Scaffold for Agentic Forecasting

DGX agent

arXiv:2609.05905v1 Announce Type: cross Abstract: LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events.

agentsarxiv-cs-lg

9 Sept 2026

FujinSplat: Seeing Through Smoke with RAW-Domain Gaussian Splatting

arXiv:2609.06017v1 Announce Type: new Abstract: The appearance of a smoky scene is shaped by two processes that a camera records together: the participating medium alters scene radiance in a view-depe

FuseDiff: Symmetry-Preserving Joint Diffusion for Dual-Target Structure-Based Drug Design

arXiv:2603.05567v2 Announce Type: replace Abstract: Dual-target structure-based drug design aims to generate a single ligand together with two pocket-specific binding poses, each compatible with a cor

Fusing Sequence Motifs and Pan-Genomic Features: Antimicrobial Resistance Prediction using an Explainable Lightweight 1D CNN-XGBoost Ensemble

arXiv:2509.23552v2 Announce Type: replace Abstract: Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenoty

Generalized infinite dimensional Alpha-Procrustes based geometries

arXiv:2511.09801v3 Announce Type: replace-cross Abstract: This work extends the recently introduced Alpha-Procrustes family of Riemannian metrics for symmetric positive definite (SPD) matrices by inco

GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learning

model-releasesarxiv-cs-ro

arXiv:2609.05927v1 Announce Type: new Abstract: Robot manipulation foundation models require scalable evaluation and data generation across diverse scenarios, with simulation providing an environment

GloVLA: Let Geometry Move and Local VLA Interact for Robust Object-Centric Manipulation in Unstructured Environments

model-releasesarxiv-cs-ro

arXiv:2609.06256v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown promising generalization for language-conditioned robot manipulation, but deploying them in unstructured

GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting

arXiv:2609.09082v1 Announce Type: new Abstract: Open vocabulary 3D semantic segmentation methods typically lift CLIP features into 3D. This embeds points in a joint vision-language space known to beha

GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models

arXiv:2512.15560v3 Announce Type: replace Abstract: The text encoder is a critical component of text-to-image and text-to-video diffusion models, fundamentally determining the semantic fidelity of the

Applications

Heat Field Signatures: From Point Clouds to Smooth Geometry

arXiv:2609.07975v1 Announce Type: new Abstract: Bringing multiscale geometric analysis directly to irregular point clouds remains difficult: quantities such as local dimension, anisotropy, density var

applicationsarxiv-cs-lg

Here's a link to the article: https://magazine.sebastianraschka.com/p/gpt-6-astra-looped-transformers-and

researchsebastian-raschka--x

Sebastian Raschka’s September 2026 article introduces **GPT‑6 *Astra***, a next‑generation language model that expands upon the Transformer backbone with a novel *looped* architecture—allowing multipl

Tutorials

HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images

arXiv:2603.23997v3 Announce Type: replace Abstract: Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics,

tutorialsarxiv-cs-cv

Hierarchical Prompt Injector for Domain Generalization Segmentation

arXiv:2609.05864v1 Announce Type: new Abstract: Domain Generalized Semantic Segmentation (DGSS) is a challenging task, as vision models often rely on low-level appearance cues that change across domai

HyCO: A Hybrid Neural Solver for Combinatorial Optimization

arXiv:2609.07990v1 Announce Type: new Abstract: Sequential reinforcement learning (RL) solvers and global diffusion model (DM) solvers for neural combinatorial optimization exhibit complementary failu

Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection

arXiv:2603.25255v2 Announce Type: replace Abstract: Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidenc

HypLTSF: A Hyperbolic Geometric View of Multi-Scale Hierarchies for Long-Term Time Series Forecasting

arXiv:2609.08286v1 Announce Type: new Abstract: Multi-scale modeling has become an effective approach for long-term time series forecasting, capturing temporal patterns that range from fine-grained lo

researcharxiv-cs-lg

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models

arXiv:2505.21465v2 Announce Type: replace Abstract: Currently, a prevalent approach for enhancing Vision-Language Models (VLMs) performance is to encode both the high-resolution version and the thumbn

researcharxiv-cs-cv

Agents

Imaginative World Modeling with Scene Graphs for Embodied Agent Navigation

arXiv:2508.06990v2 Announce Type: replace Abstract: Semantic navigation requires an agent to navigate toward a specified target in an unseen environment. Employing an imaginative navigation strategy t

agentsarxiv-cs-ro

Improving Federated Graph Recommendation with Semantic Guidance

arXiv:2606.15277v2 Announce Type: replace-cross Abstract: Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning

IXPLORE: Bounded Ideal Point Estimation with Grid-Based Uncertainty Quantification

arXiv:2609.06018v1 Announce Type: new Abstract: Ideal point estimation is widely used to analyze and visualize political data. However, selecting the corresponding spatial model involves various trade

L2G-Map: Local-to-Global Mapping via Hierarchical Diffusion Refinement and Elliptical Bayesian Fusion

arXiv:2503.02578v2 Announce Type: replace Abstract: Offline high-definition maps provide essential geometric and topological priors for autonomous driving systems. Pure-vision solutions have become th

Last week we brought LlamaParse to Claude. Now it’s available in ChatGPT, too 🦙 ChatGPT can already read PDFs. But document work gets harde…

model-releasesjerry-liu--x

Last week we brought LlamaParse to Claude. Now it’s available in ChatGPT, too 🦙 ChatGPT can already read PDFs. But document work gets harder when the information you need is buried in messy scans, den

LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery

arXiv:2609.06761v1 Announce Type: new Abstract: While diffusion models excel at capturing complex data distributions, scientific discovery often requires steering generation toward specific, uncharact

Layer Selection in VLMs for Zero-Shot OOD Detection via Multi-Resolution Entropy Estimation

arXiv:2609.08524v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts arise across institutions, acquisition pro

researcharxiv-cs-cv

Tutorials

LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies

arXiv:2609.06079v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hie

tutorialsarxiv-cs-lg

Learning Acrobatic Flight from Preferences

arXiv:2508.18817v3 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PbRL) enables agents to learn control policies without requiring manually designed reward functions,

LLM-Aided Design for Manufacturing: A Multi-Agent System for Intent-Preserving Redesign of CAD for Improved Manufacturability

arXiv:2609.05559v1 Announce Type: cross Abstract: We introduce autonomous, intent-preserving Design for Manufacturing (DFM) redesign of CAD parts: given an engineer's CAD model, the method returns a v

Local gradient neural operator

arXiv:2609.07752v1 Announce Type: new Abstract: Field temporal prediction and source identification constitute canonical problems in dynamical systems. Conventional approaches to these problems depend

LongNav-R1: Horizon-Adaptive Multi-Turn RL for Long-Horizon VLA Navigation

arXiv:2602.12351v2 Announce Type: replace-cross Abstract: This paper develops LongNav-R1, an end-to-end multi-turn reinforcement learning (RL) framework designed to optimize Visual-Language-Action (VL

safetyarxiv-cs-cv

Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation

arXiv:2609.05841v1 Announce Type: new Abstract: Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations,

MARR: Decoupling Policy, Execution, and Calibration for All-in-One Medical Image Restoration

arXiv:2609.06645v1 Announce Type: new Abstract: All-in-one medical image restoration seeks to recover heterogeneous clinical images with a single model, but PET, CT, and MRI differ substantially in de

Measuring Language Transfer in Robot Policies: Adding Greek to a Cosmos3 Vision-Language-Action Policy

model-releasesarxiv-cs-ro

arXiv:2609.07470v1 Announce Type: new Abstract: Robot foundation models are trained and evaluated predominantly in English, and robot demonstration corpora do not exist for most languages. We study th

MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting

arXiv:2609.06874v1 Announce Type: cross Abstract: High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and fo

MetaRSI / RSI2: A Meta-Recursive Self-Improving System for Recursive Self-Improving Systems Themselves

arXiv:2609.06396v1 Announce Type: new Abstract: Recursive self-improvement (RSI) lets a system improve the model-building machinery from its own failures, so every later model inherits the gain. Yet R

Mitigating Shortcut Learning: Texture-Penalized Prototype Networks

arXiv:2609.07504v1 Announce Type: new Abstract: Standard Convolutional Neural Networks (CNNs) exhibit severe performance degradation due to a strong inductive texture bias that prioritizes local, high

Hardware

MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining

arXiv:2609.05807v1 Announce Type: new Abstract: Optical Chemical Structure Recognition (OCSR) is a fundamental component of chemical literature mining, enabling molecular database construction, reacti

hardwarearxiv-cs-cv

Monocular Visual Odometry without Calibration or Test-time Optimization

arXiv:2510.03348v4 Announce Type: replace Abstract: The most accurate monocular visual odometry systems require known camera intrinsics, refine their estimates with test-time optimization, and recover

safetyarxiv-cs-cv

Monotonic Kolmogorov-Arnold Networks: A Theoretical and Empirical Study of Monotonicity as an Inductive Bias

arXiv:2606.17886v3 Announce Type: replace Abstract: Monotonicity has been a long-running architectural inductive bias for neural networks, motivated by tabular, scientific, and economic settings where

Applications

MSSP: Multi-Scale Spatially-Constrained Partition for Unsupervised Semantic Segmentation of 3D Point Clouds

arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv

applicationsarxiv-cs-cv

Multi-granularity Adaptive Hypergraph Representation Learning via Granular-ball

arXiv:2609.05574v1 Announce Type: new Abstract: Hypergraph representation learning aims to capture high-order information in graphs by constructing hyperedges that simultaneously connect multiple node

Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

safetyarxiv-cs-ro

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

researcharxiv-cs-cv

NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts

arXiv:2609.07009v1 Announce Type: cross Abstract: Multimodal continual learning has recently shown great potential for developing agents with human-like intelligence by continuously learning new tasks

NeuralLVC: Neural Lossless Video Compression via Masked Diffusion with Temporal Conditioning

arXiv:2604.03353v2 Announce Type: replace-cross Abstract: While neural lossless image compression has advanced significantly with learned entropy models, lossless video compression remains largely une

No-Regret Mixing of LRU and LFU with Optimal Switching Cost

arXiv:2609.07566v1 Announce Type: new Abstract: Caching systems often rely on simple eviction policies such as Least Recently Used (LRU) and Least Frequently Used (LFU), which perform well in compleme

Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning

arXiv:2609.06882v1 Announce Type: new Abstract: Diffusion policies offer a powerful and expressive parameterization for continuous control. Yet, their integration with reinforcement learning remains c

Novel hybrid protein scaffold gap filling using weighted machine learning ensemble, beam search, and mass-constrained reranking

arXiv:2609.05436v1 Announce Type: cross Abstract: Protein scaffold gap filling is an important computational task in protein sequence reconstruction, where missing amino acid regions must be inferred