Search: “evaluation”

Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies

arXiv:2609.28670v1 Announce Type: cross Abstract: Graph-based world models have recently emerged as a means of learning transitions over relational state representations. However, existing approaches

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Research

Broadening Uncertainty Estimation for Audio Question Answering Across Methods, Formats, and Inputs

DGX agent

arXiv:2609.28879v1 Announce Type: cross Abstract: Audio-language models can produce confident answers unsupported by the audio, motivating uncertainty estimates that identify unreliable responses. We

researcharxiv-cs-ai

25 Sept 2026

Canopy: Exploiting Piecewise Smooth Tree Priors for Multi-Fidelity Bandits

arXiv:2609.30017v1 Announce Type: cross Abstract: Many LLM inference problems, including model routing, prefix-cache management, prompt trimming, and test-time search, can be viewed as optimization ov

local-aiarxiv-cs-ai

CATCH: Counterfactual Anatomical Tissue Inpainting with Conditional Haar Diffusion

arXiv:2609.29591v1 Announce Type: cross Abstract: BraTS local synthesis replaces masked regions in T1-weighted brain MRI with plausible tumor-free tissue while preserving observed anatomy. We present

safetyarxiv-cs-ai

Context-aware Skin Cancer Epithelial Cell Classification with Scalable Graph Transformers

arXiv:2602.15783v2 Announce Type: replace Abstract: Whole-slide images (WSIs) from cancer patients contain rich information that can be used for medical diagnosis or to follow treatment progress. To a

researcharxiv-cs-cv

CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars

arXiv:2609.29075v1 Announce Type: new Abstract: Cancer registrars, including Oncology Data Specialists (ODSs), must interpret complex and frequently updated coding and staging standards. We developed

Cultural Divergence Preservation: Diagnosing Flattening and Caricature in LLM-Simulated Survey Populations

arXiv:2609.29928v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents to estimate population response distributions. In cross-cultural su

DeltaWAM: Delta World Action Models for Bimanual Manipulation

arXiv:2609.28811v1 Announce Type: new Abstract: World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and a

applicationsarxiv-cs-cv

Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

arXiv:2609.29974v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects from observational data is difficult because the most appropriate inductive bias varies with overlap, treatme

Efficient Continuous DEM Reconstruction under Limited Target-Resolution Supervision

arXiv:2609.29864v1 Announce Type: new Abstract: High-resolution digital elevation models (DEMs) support Earth observation applications, but paired training references are often available only at coars

local-aiarxiv-cs-cv

ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks

arXiv:2609.29102v1 Announce Type: new Abstract: Fully continuous diffusion language models (dLMs) denoise continuous representations without intermediate discretization, then decode all response token

safetyarxiv-cs-cl

FluidRain: Incompressible Rain Flow as an Attention Bias for Loop-in-Loop Video Deraining

arXiv:2609.29006v1 Announce Type: new Abstract: Existing video deraining methods typically exploit neighboring frames through either explicit alignment or implicit spatiotemporal aggregation. Explicit

safetyarxiv-cs-cv

From Text Decisions to Pixels: An Study of Jev-Style Visual Choice Model

arXiv:2609.29283v1 Announce Type: new Abstract: Visual software often needs a decision over supplied alternatives rather than a generated explanation. We present PixelJev, a native-image decision inte

GeoRefer-Bench: A Benchmark from Referring Pixels to Verifiable Geospatial Reasoning

arXiv:2609.29541v1 Announce Type: cross Abstract: Referring segmentation in overhead imagery is inherently relational: a query may ask for the buildings north of the road or the pond closest to a resi

Hardware

GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS

arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving

hardwarearxiv-cs-ai

GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI

arXiv:2609.30147v1 Announce Type: new Abstract: Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases. We address the challenge o

Hybrid Variational Quantum-Classical Framework with Adaptive Weighting and Efficiency Assessment

arXiv:2609.28491v1 Announce Type: cross Abstract: Hybrid quantum-classical neural networks have emerged as a promising approach for leveraging quantum computing in machine learning while mitigating cu

Large Language Models for Programming: Actually Fixing or Reimplementing Incorrect Code?

model-releasesarxiv-cs-cl

arXiv:2609.29410v1 Announce Type: new Abstract: Recent studies have shown that Large Language Models can effectively solve problems and fix bugs in diverse programming environments, including competit

Learnable Time-Frequency Masks for Explaining Time-Series Classifiers

arXiv:2609.29270v1 Announce Type: new Abstract: Time-series explainability remains challenging because discriminative information is often encoded in latent frequency or time-frequency features rather

applicationsarxiv-cs-lg

Lightweight Vision Transformer-Based U-Net for Brain Tumor Segmentation from MRI

arXiv:2609.29785v1 Announce Type: new Abstract: Accurate brain tumor segmentation from Magnetic Resonance Imaging is essential for diagnosis, treatment planning, and surgical guidance. Although Convol

local-aiarxiv-cs-cv

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their

MF-SCBO : Multi-fidelity Scalable Constrained Bayesian Optimization

arXiv:2609.29941v1 Announce Type: new Abstract: Many real-world optimization problems rely on expensive simulations or experiments, making the efficient use of available data essential. Multi-fidelity

OncoVision: Integrating Mammography and Clinical Data through Attention-Driven Multimodal AI for Enhanced Breast Cancer Diagnosis

arXiv:2511.19667v2 Announce Type: replace Abstract: OncoVision is a privileged-information training framework that uses mammography images and clinical features during training and performs inference

researcharxiv-cs-cv

Persistent Billable State: Denial-of-Wallet Attacks and Defenses in Tool-Calling LLM Agents

arXiv:2609.28585v1 Announce Type: cross Abstract: Multi-step tool-calling LLM agents rely on host runtimes to preserve state across turns. When a runtime carries an external tool return into later mod

PPTBench: Can Coding Agents Reconstruct the Visual World through Structured, Editable Slides

arXiv:2609.29718v1 Announce Type: cross Abstract: Coding agents are beginning to act in the visual world. They now build webpages, GUIs, games, 3D scenes, diagrams, and documents. Success in such visu

local-aiarxiv-cs-ai

Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents

arXiv:2609.29892v1 Announce Type: new Abstract: The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific d

Qwen3.8-27B: Using KV Cache Transplants to Boost Output Quality

model-releasesr-localllama

Since my last post, I've been thinking about different options for dynamic performance degradation, trying to squeeze as much high-quality inference out of my GPU as I can. Over the weekend I read thi

RAPID: Robot Agentic Programming from Demonstrations

arXiv:2609.30249v1 Announce Type: cross Abstract: Coding agents have demonstrated enormous success in solving complex programming problems. To leverage their potential for robot systems, this work int

RGBD20K: A Large-Scale Benchmark for RGB-D Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.29028v1 Announce Type: new Abstract: In this paper, we propose RGBD20K, a novel dataset for facilitating the development of more robust and general RGB-D semantic segmentation by encompassi

Robust Detection of LLM-Generated Text under Contamination

arXiv:2609.29935v1 Announce Type: cross Abstract: We study the detection of LLM-generated text under editing and contamination. Modeling human and machine text as finite-order Markov processes with Hu

Agents

S2Planner: Multi-Scale Semantic Planner for End-to-End Autonomous Driving

arXiv:2609.29813v1 Announce Type: cross Abstract: We present S2Planner, a trajectory planner that combines three front-facing cameras with ego-motion history and the current driving command. A fine-tu

agentsarxiv-cs-ai

Safe Skill Retirement for Physical Agents

arXiv:2609.29543v1 Announce Type: new Abstract: Agent skills bundle procedural guidance with execution conditions governing authority, user consent, and live environment state. When model capabilities

Spooftral: Can Voxtral Audio-Language Model Detect Speech Spoofing?

arXiv:2609.28713v1 Announce Type: cross Abstract: Self-supervised learning (SSL) countermeasures (CMs) have shown strong performance in recent years. However, they often show degraded performance whil

researcharxiv-cs-cl

Spot, Separate, and Enhance: Fully Generative Approach for Audio Mixing

arXiv:2609.29169v1 Announce Type: cross Abstract: We introduce Spot, Separate, and Enhance (SSE), the first multimodal, user-guided generative model for audio remixing and enhancement. SSE enhances vi

STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.29607v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have advanced video understanding, they remain highly prone to hallucinations in dynamic scenes. We arg

SwitchPFN: Shared Switching Dynamics for Frozen In-Context Time Series Classification

arXiv:2609.29814v1 Announce Type: new Abstract: Tabular foundation models (TFMs) provide a promising route to time-series classification, but their effectiveness depends on how sequential data are con

Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data

arXiv:2505.15465v2 Announce Type: replace Abstract: This paper introduces Synthetic Enclosed Echoes (SEE), a novel dataset designed to enhance robot perception and 3D reconstruction capabilities in un

applicationsarxiv-cs-ro

The era of omni agents is upon us. This is a great report by the Qwen Team on their omni-modal agents. They present Qwen3.8-Omni-Flash, a na…

The era of omni agents is upon us. This is a great report by the Qwen Team on their omni-modal agents. They present Qwen3.8-Omni-Flash, a natively multimodal model trained for long-horizon agent tasks

model-releasesdair-ai--x

Transformers as Cross-Task Learners: Shared Structure Drives Sample Efficiency in In-Context Learning

arXiv:2609.29060v1 Announce Type: cross Abstract: Transformers achieve remarkable performance by jointly learning broad families of tasks during pretraining and adapting to unseen tasks from only a sh

researcharxiv-cs-lg

UNWIND: Any-Length Facial Video for Stress Detection without Temporal Windowing

arXiv:2609.29553v1 Announce Type: cross Abstract: Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods di

VietPrism: A large-scale Vietnamese speech and deepfake corpus with diverse dialects and code-switching

arXiv:2609.30005v1 Announce Type: new Abstract: Vietnamese speech research is constrained by resources that isolate automatic speech recognition from speaker, dialect, code-switching, and deepfake ana

applicationsarxiv-cs-cl

When Explanations Cannot Be Read: Measuring and Correcting SHAP and LIME Rendering for Right-to-Left Languages

arXiv:2609.28565v1 Announce Type: cross Abstract: Post hoc explanation methods such as SHAP and LIME are widely used to interpret text classifiers, but their visualizations are mainly designed for lef

When Honesty is Not Enough in AI Debate

arXiv:2609.29189v1 Announce Type: new Abstract: Scalable oversight aims to verify the behaviour of agents whose capabilities exceed those of their overseers. AI debate has been proposed as an oversigh

safetyarxiv-cs-ai

When Identical Rows Disagree: From Benchmark Identifiability to Replication-Robust Anomaly Detection

arXiv:2609.29580v1 Announce Type: new Abstract: A released table is often treated as an i.i.d. sample, although its repeated rows may encode business frequency, repeated entities, joins, resampling, o

Agents

Where Cyber Agents Struggle: Bottleneck Analysis of Multi-Stage LLM Agents

arXiv:2609.28572v1 Announce Type: cross Abstract: Multi-stage LLM-based cyber agents may complete attack workflows while remaining brittle, costly, or reliant on incorrect interpretations of execution

agentsarxiv-cs-ai

A comparative assessment of global building and settlement datasets across geographic and settlement contexts

model-releasesarxiv-cs-cv

arXiv:2609.28154v1 Announce Type: new Abstract: Global building and settlement datasets increasingly support population mapping, exposure assessment, urban monitoring, and other analyses of the built

24 Sept 2026

Hardware

A Scaling Study for fMRI Foundation Models

arXiv:2609.27232v1 Announce Type: new Abstract: Scaling laws have guided large-model development in computer vision and natural language processing, but the relationships among data, model size, and c

hardwarearxiv-cs-lg

24 Sept 2026

Tutorials

Active Learning for Biodiversity Monitoring: From Label Efficiency to Reliable Ecological Inference