Search: “evaluation”

6.5% of the Neuro-Symbolic Literature Can Be Reproduced from Its Published Artifacts, a Six-Stage Audit Framework and First Instantiation

arXiv:2608.26236v1 Announce Type: new Abstract: We present a six-stage framework for auditing the reproducibility of scientific claims across a research literature within the computer science domain,

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Model Releases

A Layer Importance Metric for Quantization Accounting for the Speed-Quality Trade-off in Autoregressive Models

DGX agent

arXiv:2608.26926v1 Announce Type: new Abstract: Small language models (sLLMs) are nowadays hosted on devices with limited memory and computational budget. In an autoregressive setup, inference is memo

model-releasesarxiv-cs-lg

28 Aug 2026

Hardware

A Survey of LLM Prompt Datasets: Taxonomy, Linguistic Patterns, and Practical Uses

arXiv:2510.09316v3 Announce Type: replace-cross Abstract: We compile 129 public LLM prompt datasets with more than 1.22TB and more than 673M instances and organize them into a unified taxonomy. We use

hardwarearxiv-cs-cl

Applications

A Table Is Worth 64 Tokens: Pixel-level Compression for Multi-Table Document Question Answering

arXiv:2608.26949v1 Announce Type: new Abstract: Answering questions over real-world documents requires processing long inputs that interleave text with tables. Optical context compression, which repre

applicationsarxiv-cs-ai

A Very Big Video Reasoning Suite

arXiv:2602.20159v3 Announce Type: replace-cross Abstract: Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grou

Adversarial Training Without Input Gradients via Low-Rank Householder Expansions

arXiv:2608.26963v1 Announce Type: new Abstract: This work concerns adversarial training against the small-norm adversarial examples that arise from the inherent input instability of a trained deep neu

researcharxiv-cs-lg

Agent Mesh: Reliability Primitives for Non-Idempotent Agent Delegation - Identity Adequacy and Evidence Adequacy

arXiv:2608.26225v1 Announce Type: new Abstract: Autonomous agents increasingly perform bounded software tasks under an orchestrator that retries, resumes, and budgets them. The machinery such orchestr

agentsarxiv-cs-ai

Agentic AI for operating scientific instruments for nanoscale characterization

arXiv:2608.26198v1 Announce Type: new Abstract: Operating a scientific instrument such as an atomic force microscope (AFM) requires continuous expert decision-making. A trained user defines the experi

agentsarxiv-cs-ai

Agents Don't Paginate: First-Chunk Selection for LLM Tool Responses

model-releasesarxiv-cs-cl

arXiv:2608.26130v1 Announce Type: new Abstract: Coding agents built on large language models (LLMs), such as Claude Code, Cursor, OpenAI Codex, GitHub Copilot, and Aider, receive tool responses that r

Aphanta: Diagnosing Task-Aligned Image-Edited Intermediates for Multimodal Reasoning

model-releasesarxiv-cs-cv

arXiv:2608.26993v1 Announce Type: new Abstract: Explicit visual intermediates can help multimodal large language models (MLLMs) externalize spatial evidence and updated visual states, but their utilit

Are Large Language Models Effective Knowledge Graph Constructors?

model-releasesarxiv-cs-cl

arXiv:2510.11297v2 Announce Type: replace Abstract: Knowledge graphs (KGs) are widely used in knowledge-intensive applications, yet it remains unclear how effectively current large language models (LL

Artificial Intelligence Models Can Predict and Collaboratively Modulate Human Memory Search

arXiv:2608.26152v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many langu

Benchmarking_Fast_Domain_Adaptation_for_Unsupervised_Speech_Units

arXiv:2608.26992v1 Announce Type: new Abstract: Representation learning has attracted great atten- tion and managed to reach good performances as a pretraining method for downstream tasks or as a firs

Beyond Execution: Auditing Experimental Fidelity in LLM-Driven Scientific Research

arXiv:2608.26753v1 Announce Type: cross Abstract: LLM agents used for scientific experimentation must do more than generate executable code: they must implement the reference method faithfully, design

Local Ai

BLANC: Discovering Patent White Space via Changes in Normalized Pointwise Mutual Information Between Multi-View Clusters

arXiv:2608.26685v1 Announce Type: cross Abstract: Identifying white space --- the unexplored but potentially valuable regions of a patent landscape --- is essential for strategic R&D planning, yet exi

local-aiarxiv-cs-cl

Applications

BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI

arXiv:2608.27149v1 Announce Type: new Abstract: Conversational AI systems, such as chatbots and virtual assistants, are becoming increasingly important to digital business processes. However, the esta

applicationsarxiv-cs-ai

Bregman Linearized Augmented Lagrangian Method for Nonconvex Constrained Stochastic Zeroth-order Optimization

arXiv:2504.09409v2 Announce Type: replace-cross Abstract: In this paper, we study nonconvex constrained stochastic zeroth-order optimization problems, for which we have access to exact information of

Calibrated Enough to Know, Not Calibrated to Act: Fabricated Evidence Makes LLM Agents Commit to the Unknowable

arXiv:2608.27167v1 Announce Type: new Abstract: An LLM agent shown a professional-looking market panel commits to a directional call on a provably unpredictable question far more often than one asked

agentsarxiv-cs-ai

Case2Flow: Bridging Patient Cases and Guideline Flowcharts through Multimodal Retrieval

arXiv:2608.26414v1 Announce Type: new Abstract: Medical guidelines encode rich, evidence-based decision logic, yet the specific decision artifact a clinician needs is hard to locate within a guideline

safetyarxiv-cs-cl

CLIPPER: Replayable Shortlisted Optimization for Repeated Spatial Coverage Planning

arXiv:2608.26819v1 Announce Type: new Abstract: Operational requirements developed with the City of Braunschweig frame municipal micromobility planning under geofenced exclusions, mandatory retained s

safetyarxiv-cs-ro

Co-Evolving Structured Knowledge and Reasoning in Language Models

arXiv:2608.26386v1 Announce Type: cross Abstract: Retrieval-augmented methods improve factual accuracy by grounding language models in external knowledge, but retrieving over unstructured text often i

Common Geodesics Do Not Guarantee Fisher Consistency of the Structured SVM: Minimal Counterexamples and a Tree-Metric Classification

arXiv:2608.27203v1 Announce Type: new Abstract: A known necessary condition for Fisher consistency of the structured support vector machine requires the task loss to be a metric for which every output

researcharxiv-cs-lg

Contact-Aided Factor-Graph Localization for Underwater Sampling

arXiv:2608.26932v1 Announce Type: new Abstract: Accurate state estimation for autonomous underwater vehicles performing close-range seafloor sampling remains challenging. In low-altitude operation, do

agentsarxiv-cs-ro

Cross-Platform Benchmark of Neural 3D Reconstruction for Autonomous Laboratory Robots

model-releasesarxiv-cs-ro

arXiv:2608.26383v1 Announce Type: new Abstract: Autonomous robots performing laboratory tasks depend on 3D reconstruction pipelines that can turn raw camera streams into actionable object representati

Decoupling Planning and Control for Instructable Agents

arXiv:2608.26788v1 Announce Type: new Abstract: Recent work shows that pre-trained, instruction-tuned vision-language models (VLMs) perform well at mapping from instructions and observations to high-l

safetyarxiv-cs-ai

DEEPCHART: How Far are LLMs from Faithful Data-Science Chart Generation?

arXiv:2608.26757v1 Announce Type: new Abstract: Faithful chart generation in real-world data-science workflows requires grounding visualizations in scattered evidence, computing chart-ready quantities

Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference

arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through itera

researcharxiv-cs-cl

Differentiable Jitter Correction using Deep Learning-based Image Quality Metric for Phase-Contrast Micro-CT

arXiv:2608.27034v1 Announce Type: new Abstract: This paper proposes a fully differentiable jitter correction method for X-ray phase-contrast micro computed tomography using a deep learning-based image

researcharxiv-cs-cv

Diffusion Policies for Short-Horizon Planning in Robot Crowd Navigation

arXiv:2608.27158v1 Announce Type: new Abstract: Robot crowd navigation requires safe and efficient decision-making under dense, dynamic, and multimodal human--robot interactions. Existing reinforcemen

Dispersive Forward Tree Search for Optimal Control: Coverage, Complexity, and Computation

arXiv:2608.26314v1 Announce Type: new Abstract: Steering-based planners require solutions to state-to-state boundary value problems, which can be inaccessible for nonlinear platforms. Forward propagat

researcharxiv-cs-ro

District-Level Food Environment Indicators and Social Vulnerability in Sao Paulo

arXiv:2608.26299v1 Announce Type: cross Abstract: Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities. This study ex

researcharxiv-cs-lg

Do Coding Agents Need Executable World Models, Simplification, and Verification to Solve ARC-AGI-3?

arXiv:2607.15439v2 Announce Type: replace Abstract: Our previous ARC-AGI-3 agent bundled executable world modeling, prompted simplification, and exact replay verification, leaving their individual con

Tutorials

Domain-Specific Self-Supervised Representation Learning for Retinal Fundus Classification

arXiv:2608.26686v1 Announce Type: new Abstract: Despite the growing number of public datasets, annotated medical images remain scarce. Supervised learning methods achieve strong performance on many be

tutorialsarxiv-cs-cv

DPA-I2P: Depth-Guided Projective Alignment for Image-to-Point-Cloud Registration in Autonomous Driving

arXiv:2608.26589v1 Announce Type: new Abstract: Image-to-Point Cloud Registration aims to estimate the camera pose of a given image within a 3D scene point cloud, which is a fundamental task in autono

safetyarxiv-cs-cv

Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras

arXiv:2510.04802v2 Announce Type: replace-cross Abstract: Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape c

safetyarxiv-cs-ai

Embodied Scene Rearrangement Planning

model-releasesarxiv-cs-ro

arXiv:2608.27371v1 Announce Type: new Abstract: This paper introduces Embodied Scene Rearrangement Planning (ESRP), a novel task requiring embodied agents to rearrange furniture in 3D scenes to match

Emotional Preferences as Goal-Priority Regulation

arXiv:2608.27072v1 Announce Type: cross Abstract: A core question in decision-making for agents is whether the relative priorities of competing lower-level objectives can be determined by emotional pr

safetyarxiv-cs-ai

Equal Ranking Quality, Different Decisions: Training Order-Consistent LLM Scorers

arXiv:2608.26762v1 Announce Type: new Abstract: Rerankers, reward models and multi-document QA scorers score candidate documents or responses in one LLM prompt, so each score depends on their order. S

researcharxiv-cs-cl

Local Ai

Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

local-aiarxiv-cs-ai

FaultLens: Learning Compact Behavioral Test Suites for Generated Operational Programs

arXiv:2608.26746v1 Announce Type: cross Abstract: Generated operational programs are often validated with either a few hand-written examples or exhaustive regression suites. The former can miss sparse

Fine-Tuning of Transformer models with Frames

arXiv:2608.26430v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) strategies such as Low-Rank Adaptation (LoRA) are effective solutions for fine-tuning large-scale pre-trained mod

FIRSTPASS: A Multi-Domain, Multi-Round Peer Review Dataset Grounded in Real Editorial Outcomes

arXiv:2608.26129v1 Announce Type: cross Abstract: Scientific peer review datasets have trained AI systems exclusively on Computer Science and Machine Learning venues, producing models that critique ab

FoldPipe: Bounded Remote Streaming of Native Molecular Shards with Asynchronous Prefetch

arXiv:2608.27029v1 Announce Type: cross Abstract: Training molecular machine-learning models on ephemeral or memory-constrained accelerator instances can require repeatedly retrieving preprocessed mol

Forward-Free Diffusion Language Models with BPTT-Free Looped Refinement

arXiv:2606.08357v2 Announce Type: replace Abstract: Diffusion language models generate text through iterative denoising, offering a powerful alternative to autoregressive generation. However, discrete

researcharxiv-cs-cl

From Accuracy to Robustness: A Study of Rule- and Model-based Verifiers in Mathematical Reasoning

arXiv:2505.22203v3 Announce Type: replace-cross Abstract: Trustworthy verifiers are essential for the success of reinforcement learning with verifiable reward (RLVR), which is the core methodology beh

From Reasoning to Pixels: Grounded Medical Multimodal LLMs for VQA and Segmentation

arXiv:2608.26856v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have demonstrated impressive performance in Medical Visual Question Answering (Med-VQA), their relia

Applications

From Sound to Symptom: Real-Time Respiratory Signal Understanding for Conversational Healthcare Agents

arXiv:2608.26163v1 Announce Type: cross Abstract: Cough events during live spoken conversations carry clinically valuable respiratory signals, yet existing dialogue systems treat them as acoustic nois

applicationsarxiv-cs-ai

FU-Mamba: A Frequency-Enhanced Dynamic Scanning Framework for Oralscan Image Segmentation

arXiv:2608.26607v1 Announce Type: new Abstract: Oralscan image segmentation is essential for computer-aided diagnosis and treatment planning in digital dentistry. However, existing visual state space

researcharxiv-cs-cv