Search: “benchmark”

Graph-Based Stochastic Power-UCT: Monte-Carlo Graph Search with Power Mean Estimation

arXiv:2609.19956v1 Announce Type: new Abstract: Tree-based Monte-Carlo Tree Search (MCTS) duplicates the same state when it is reached through different trajectories, which can waste simulations in st

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How to upskill enterprise AI builders by using daily micro habits

DGX agent

As enterprises invest in generative AI, tech leaders keep seeing the same pattern: Developers test AI tools for a week, hit setup problems, and then drift back to the backlog. Nothing ships. The real

model-releasesgoogle-cloud-ai

18 Sept 2026

HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification

model-releasesarxiv-cs-cv

arXiv:2609.19755v1 Announce Type: cross Abstract: Accurate classification of brain disorders from neuroimaging data remains challenging because of substantial inter-subject heterogeneity and the compl

Hypernetwork-Parameterized Spatially Adaptive Neural Operators for PDE Learning

arXiv:2609.20309v1 Announce Type: new Abstract: Spatially heterogeneous partial differential equations (PDEs) exhibit location-dependent dynamics arising from variations in geometry and physical coeff

researcharxiv-cs-lg

Improving Generalization and Robustness in Offline Reinforcement Learning via Boundary-Aware Data Augmentation

arXiv:2609.20300v1 Announce Type: new Abstract: Current offline reinforcement learning (ORL) algorithms tend to overfit the training dataset and exhibit poor in-distribution generalization and robustn

Improving Offline Goal-Conditioned Reinforcement Learning via Selective Reward Stimulation

arXiv:2609.19414v1 Announce Type: new Abstract: Goal-conditioned reinforcement learning aims to learn policies that reach specified goals, but remains challenging in offline settings with sparse rewar

Interpretable and Calibrated Classification of Clinical Data Using Supervised Feature Binarization

arXiv:2607.15394v2 Announce Type: replace Abstract: Black-box models limit the adoption of artificial intelligence in medicine because their predictions are difficult to interpret and reproduce. We pr

Large Language Models as Falsifiers for Cyber-Physical Systems

arXiv:2609.20752v1 Announce Type: cross Abstract: Falsification searches for counterexamples to formal specifications in cyber-physical systems (CPS). With specifications written in Signal Temporal Lo

Learn Before You Judge: Progressive Knowledge-to-Decision Alignment for Explainable Hateful Meme Detection

arXiv:2609.19778v1 Announce Type: new Abstract: Hateful memes spread abusive content through implicit interactions between images and text, posing serious threats to the safety of online communities.

safetyarxiv-cs-cl

Learning-Based Reconstruction of Optical Properties in Bilayered Media from Single-distance Time-Resolved Reflectance Measurements

arXiv:2609.19786v1 Announce Type: new Abstract: The inverse problem of reconstructing optical properties, specifically absorption and scattering coefficients, in layered biological media from time-dom

LLM-as-an-Improver: Turning Verification into Better Candidates

arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. Howe

Marginal utility, matrix factorization, and the Key-Value (KV) cache: a unified information-economic framework for sovereign geo-mining inference

arXiv:2609.20068v1 Announce Type: new Abstract: This paper builds a theoretical bridge between the economic notion of marginal utility and two machine-learning constructs, matrix factorization and the

Minimax-Optimal Online Contract Design with Unrestricted Bounded Contracts

arXiv:2609.20353v1 Announce Type: new Abstract: We study repeated contract design when a principal observes outcomes but not the actions that generate them. The principal may use any bounded outcome-c

MiX: Micro-Inverted-Scaling for End-to-End Low-Bit Vision-Language Model Acceleration

arXiv:2609.19683v1 Announce Type: cross Abstract: The deployment of Vision-Language Models (VLMs) on edge devices is severely bottlenecked by memory bandwidth, necessitating aggressive sub-8-bit quant

MoSSGate: Memory-Modulated State-Space Gating for Skin Lesion Segmentation

arXiv:2609.20181v1 Announce Type: new Abstract: Accurate skin lesion segmentation is crucial for reliable computer-aided dermatological diagnosis, yet existing convolutional and transformer-based mode

Local Ai

MTF-Net: Multi-Modal Temporal Feature Fusion Network for Pedestrian Intention Prediction

arXiv:2609.20178v1 Announce Type: new Abstract: Accurately predicting pedestrian intentions is crucial for ensuring safe and proactive interaction between autonomous vehicles and pedestrians. However,

local-aiarxiv-cs-cv

Navi-Agent: Unlocalized Monocular Navigation Agent

model-releasesarxiv-cs-cv

arXiv:2609.20388v1 Announce Type: cross Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to execute long-horizon instructions in unknown environments

NeuSOGA3D: A Neuro-Symbolic Framework for Explainable 3D Geometric Reconstruction

arXiv:2609.20323v1 Announce Type: new Abstract: Three-dimensional reconstruction from unorganized point clouds remains a challenging problem in computer vision, geometric modeling, and computer-aided

Tutorials

Not All Layers Are Equal: Dynamic Layer Routing for Reliable CLIP OOD Detection

arXiv:2609.20299v1 Announce Type: new Abstract: Information aggregation across model layers are revealed to improve OOD detection. In contrast to crafting a method for layer-wise information aggregati

tutorialsarxiv-cs-cv

Not All Nodes Are Created Equal: Homophily-Aware Stratification for Stable GNN Evaluation

arXiv:2609.19210v1 Announce Type: cross Abstract: Graph neural networks are widely used for transductive node classification, with accuracy typically measured on randomly drawn train/validation/test s

Online Supervised Dimension Reduction with Random Features: Diagnostics and Computational Trade-offs

arXiv:2609.20454v1 Announce Type: cross Abstract: Accurate optimization of a supervised spectral objective need not produce an accurate population subspace or a better predictive representation. We in

researcharxiv-cs-lg

Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings

arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi

Paint-Anything: Unified Any-Color Control for Image Generation and Editing

arXiv:2609.20816v1 Announce Type: cross Abstract: Professional design requires any-color control: the ability to specify an object's target color with any 24-bit hex value for image generation and edi

PAPC: Platform Mediation for Privacy-Propagation Externalities in AI-Mediated Workflows

arXiv:2609.19226v1 Announce Type: cross Abstract: AI-mediated platforms coordinate work through LLM agents acting for different principals. In these workflows, privacy loss can be created before a fin

safetyarxiv-cs-ai

PerSeM: Persistent Semantic Memory for Long-Horizon Open-Vocabulary UAV Mapping

arXiv:2609.19542v1 Announce Type: new Abstract: Open-vocabulary segmentation enables rich semantic perception for UAVs, but frame-wise predictions can remain temporally inconsistent across repeated ob

Predict Before You Deploy: Offline Prediction of Quantization-Induced Task Degradation for World Action Models

arXiv:2609.19441v1 Announce Type: cross Abstract: World action models (WAMs) rely on video-generation backbones, requiring substantial memory and compute for deployment. Post-training quantization red

QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization

arXiv:2609.20156v1 Announce Type: cross Abstract: Ubiquitous time series data across diverse domains enables critical applications in areas such as transportation systems and power grids. Recently, tr

Quantifying Mechanical Intelligence in Legged Robots with Information Theory

model-releasesarxiv-cs-ro

arXiv:2609.19588v1 Announce Type: new Abstract: Mechanical intelligence, loosely defined as the reduction in control burden afforded by a robot's physical form, has become a prominent concept in robot

Quantum Graph Convolutional Networks: Implementation and Trainability Analysis

arXiv:2609.19983v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) achieve state-of-the-art performance on graph-structured data, but training and inference on large graphs are often bottl

QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning

arXiv:2602.04620v3 Announce Type: replace Abstract: GRPO-style reinforcement learning (RL)-based LLM fine-tuning algorithms have recently gained popularity. Relying on heuristic trust-region approxima

Question: UkisAI Swift Ternary Bonsai 2 27B?

model-releasesr-localllama

Hey community, Jovan from UkisAI here, We're the team behind Swift Qwen3.8 27B, the Qwen model with token usage and overthinking error improvements Our estimate is that we can make a great improvement

QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training

arXiv:2609.19513v1 Announce Type: new Abstract: High-quality pre-training data is a critical bottleneck for educational and STEM-specific language models targeting edge AI and on-device deployment whe

Reach or Solve? Attributing Agentic RL Gains with Checkpoint Handoffs

arXiv:2609.19636v1 Announce Type: new Abstract: Reinforcement learning now trains language-model agents that act over dozens of steps in live environments. The gains are large, and they are read as be

Reflective Recovery: A Self-Supervised Method for Reasoning by Learning from Mistakes

model-releasesarxiv-cs-cl

arXiv:2609.19156v1 Announce Type: new Abstract: Data-driven fine-tuning is widely adopted to enhance reasoning in Large Language Models (LLMs) due to its simplicity and efficiency. However, mainstream

Local Ai

Region-Level Policy Optimization for Fine-grained MLLM Perception

arXiv:2609.19745v1 Announce Type: new Abstract: Fine-grained visual perception in MLLMs is commonly improved by raising the resolution, but the added visual tokens inflate vision-encoding and language

local-aiarxiv-cs-cv

Reimagining service delivery in the agentic era with Google Public Sector

model-releasesgoogle-cloud-ai

State and local governments are driven by a shared mission to provide responsive, equitable, and accessible services. However, achieving this goal is often hindered by legacy technical debt, disconnec

Relational Attention for Data-Efficient Language Modeling

arXiv:2609.20530v1 Announce Type: new Abstract: We present Relational BabyLM, a system submission to the BabyLM 2026 challenge that combines two cognitively motivated inductive biases in a single deco

researcharxiv-cs-cl

Replan, Repair, or Edit? A Unified Empirical Evaluation of Travel Agents for Itinerary Revision under Resource Disruptions

arXiv:2609.19654v1 Announce Type: new Abstract: Travel-planning agents generate itineraries that may become infeasible after acceptance because of flight cancellations, hotel unavailability, or attrac

Agents

Rethinking Multi-Agent Collaboration: When More Is Less

arXiv:2609.19759v1 Announce Type: new Abstract: The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question

agentsarxiv-cs-ai

Robust Conformal Intrusion Detection via Traffic-Aware Calibration and Attack-Orbit Invariance

arXiv:2609.19241v1 Announce Type: cross Abstract: Large language models fine-tuned for network intrusion detection emit single-point predictions without statistical validity guarantees. Conformal pred

Hardware

S4R: Scaling for Rigid-Body Interpenetration Resolution

arXiv:2609.20524v1 Announce Type: cross Abstract: Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such a

hardwarearxiv-cs-ro

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces

arXiv:2607.18554v2 Announce Type: replace-cross Abstract: Learning local policies for continuous networked systems requires accounting for the effects of decisions beyond each agent's observation neig

ScientistTwo: Pioneering the Human Knowledge Frontier with Autonomous AI

arXiv:2609.19644v1 Announce Type: new Abstract: Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate visi

Tutorials

Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization

arXiv:2609.19476v1 Announce Type: new Abstract: Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual scr

tutorialsarxiv-cs-lg

SETTer: Sparse-Encoder Transformer for Long-term Multivariate Time Series Forecasting

arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi

SIMLIFE: Pattern Understanding for Long-Horizon Human-Agent Partnership

arXiv:2609.19610v1 Announce Type: new Abstract: Understanding humans over long horizons requires agents to infer not only what people need in the moment, but also how routines form, why they repeat, a

Agents

SLAMSqueezeBench: Comparing SLAM Systems under Resource Constraints

arXiv:2609.19533v1 Announce Type: new Abstract: Simultaneous localization and mapping (SLAM) is one of the services running on an autonomous robot. It is typically run to assist other tasks such as pl

agentsarxiv-cs-ro

Socialized UAV Cross-Task Learning: Towards Cross-Granularity Collaboration through Hierarchical Interaction

model-releasesarxiv-cs-cv

arXiv:2609.19867v1 Announce Type: new Abstract: Joint learning across heterogeneous tasks is often treated as task coupling through feature sharing, distillation, or auxiliary supervision. However, in