Search: “evaluation”

All of AI benchmarking at your fingertips

IBM, as part of a global effort, is developing tools to streamline AI benchmarking by making results easier to compare, validate, and reuse. The initiative is detailed in a blog post titled 'All of AI

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AlphaRoute: Large Language Models as Semantic Optimizers for Multi-Objective Routing

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arXiv:2607.19768v1 Announce Type: new Abstract: Very Large Scale Integration (VLSI) global routing is an NP-hard combinatorial optimization problem requiring signal net assignment across capacity-cons

safetyarxiv-cs-lg

23 Jul 2026

Hardware

Anatomy-Aware 3D Mesh Refinement of Pericardium Segmentations on Computed Tomography

arXiv:2607.19210v1 Announce Type: new Abstract: Accurate delineation of the pericardium in a cardiac CT scan is essential for quantifying epicardial adipose tissue, yet it remains one of the most chal

hardwarearxiv-cs-cv

Benchmarking Confidential GPU Inference on NVIDIA H100 under Intel TDX

arXiv:2607.19353v1 Announce Type: new Abstract: Confidential computing is becoming a practical deployment requirement for AI inference workloads that process sensitive inputs or protect proprietary mo

Tutorials

Beyond Fail-to-Pass: Iterative Hardening of Co-Generated Bug Reproduction Tests and Fixes

arXiv:2607.19843v1 Announce Type: cross Abstract: Large language models (LLMs) have made automated program repair (APR) increasingly practical for real-world bugs, but repairing directly from bug repo

tutorialsarxiv-cs-ai

Boltzmann-Expected Molecular Design with Decoupled Annealing Flows

arXiv:2607.19519v1 Announce Type: cross Abstract: Most 3D properties relevant to molecular design, including free energies and shape descriptors, are extit{expectations} over the Boltzmann distributio

Bounding Boxes to Improve Small Language Model Performance on Vision-Based Grading Tasks

arXiv:2607.18767v1 Announce Type: new Abstract: The deployment of Small Language Models (SLMs) in educational settings offers significant advantages in terms of privacy, cost, and scalability. However

researcharxiv-cs-cv

BRIM: Workload-Balanced Dual-Sided Bit-Serial Sparse Inference Accelerator

arXiv:2607.19431v1 Announce Type: cross Abstract: Bit-serial accelerators exploit bit-level sparsity to reduce DNN inference cost, but existing designs exploit sparsity on only one operand, bounding t

ChannelGuard: Safe Models Do Not Compose into Safe Multi-Agent Systems

arXiv:2607.19430v1 Announce Type: cross Abstract: Multi-agent LLM applications chain a planner, worker agents, a verifier, and a synthesizer, and every hop between agents is an unmonitored channel thr

CLARK: Closed-loop Learning for Adaptive Reasoning over Knowledge Graphs

arXiv:2607.19996v1 Announce Type: new Abstract: Machine Learning models are widely used for automating classification tasks by extracting statistical patterns from data. However, their performance det

Clinical Pathways as Safety Specifications for Physical AI in Hospital Wards

arXiv:2607.19827v1 Announce Type: new Abstract: Ensuring safety in Physical AI systems operating in real-world environments is a critical challenge, particularly in hospital wards where vulnerable pat

safetyarxiv-cs-ro

Closing the Lab-to-Store Gap: A Data-Efficient Post-Training and Experience-Driven Learning VLA Framework for Retail Humanoids

arXiv:2607.20345v1 Announce Type: cross Abstract: Closing the gap between benchmark performance and reliable real-world operation remains a central challenge for Vision-Language-Action (VLA) humanoid

Local Ai

CNS-Edit++: Category-Agnostic 3D Editing with Coupled Neural Shape Representation

arXiv:2607.16577v2 Announce Type: replace Abstract: This paper presents a latent-space 3D shape editing framework built upon a coupled neural shape (CNS) representation and a neural feature volume opt

local-aiarxiv-cs-cv

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection

arXiv:2512.16300v3 Announce Type: replace Abstract: Existing image forgery detection (IFD) methods either exploit low-level, semantics-agnostic artifacts or rely on multimodal large language models (M

Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation

arXiv:2607.15434v3 Announce Type: replace-cross Abstract: Multi-agent systems routinely place one AI agent in authority over another. When a subordinate refuses a task, the manager chooses the outcome

Cognitive Dual-Process Planning for Autonomous Driving with Structured Scene Knowledge and Verifiable Reasoning-Action Consistency

arXiv:2607.19194v2 Announce Type: cross Abstract: High-level planning for autonomous driving is a knowledge-intensive engineering decision task that requires accurate scene understanding, timely infer

Confidence-Gated Vision-Only Heading Alignment for UAV-UGV Cooperative Systems

arXiv:2607.18713v1 Announce Type: cross Abstract: Vision-based heading prediction is useful for UAV--UGV cooperation, but accurate prediction alone does not guarantee that every predicted heading shou

Congestion-Aware Robot Tour Planning in Crowded Environments

arXiv:2606.19031v2 Announce Type: replace Abstract: Autonomous mobile service robots are often required to complete tours that require navigating through a set of locations in an environment. Example

agentsarxiv-cs-ro

Contact-Persistent Full Actuation for Aerial Physical Interaction

arXiv:2607.19708v1 Announce Type: new Abstract: Fully actuated unmanned aerial vehicles (UAVs) are usually certified through rank conditions on a control-allocation matrix or through free-flight track

safetyarxiv-cs-ro

Continual Video-MLLM Adaptation over Evolving Domains

arXiv:2607.18716v1 Announce Type: new Abstract: Video multimodal large language models have shown strong capability in video understanding, yet their adaptation to sequentially evolving domains remain

Courteous Anticipation: Improving Long-Lived Task Planning in Persistent Shared Environments

arXiv:2607.20289v1 Announce Type: cross Abstract: We consider a task planning scenario in which robots sharing a persistent environment are assigned tasks one at a time from a held-out sequence. Stand

CR-Refiner: An Object-Centric Optimal Transport Reranker for Edit-Conditioned 3D Scene Retrieval

arXiv:2607.19115v1 Announce Type: new Abstract: Edit-conditioned 3D scene retrieval pairs a reference 3D room with a natural-language modification and retrieves rooms from a corpus that satisfy the ed

Cross-Dataset Generalization in Breast MRI Tumor Classification via Class-Wise Dataset Mixing

arXiv:2607.18678v1 Announce Type: new Abstract: Breast MRI is highly sensitive for detecting breast tumors, but exams contain many slices and require substantial reading time. Deep learning models oft

Cross-Modal UAV Object Tracking: State-Aware Representation Learning and A Unified Benchmark

arXiv:2607.18768v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) object tracking has emerged as a popular research field with broad practical applications. Modern UAVs are increasingly eq

Cross-Subject Semantic Decoding with Shared-Space Alignment for Generalized Neural Representation Learning

arXiv:2607.19394v1 Announce Type: cross Abstract: Generalizing across subjects remains challenging in invasive neural recordings because electrode configurations, anatomical structures, and neural sig

safetyarxiv-cs-ai

CruiseBench: A Real-Flight-Aligned N-CMAPSS Benchmark for Engine RUL Prediction

model-releasesarxiv-cs-lg

arXiv:2607.19380v1 Announce Type: new Abstract: Remaining useful life (RUL) prediction estimates how long an engine can continue safe operation and is central to maintenance planning. N-CMAPSS extends

Deep Learning Estimation of Sex, Age, Height, and Weight from CT-derived Digitally Reconstructed Radiographs

arXiv:2607.18638v1 Announce Type: new Abstract: Purpose: To develop and validate a deep learning ensemble for estimating adult sex, age, height, and weight from coronal digitally reconstructed radiogr

researcharxiv-cs-cv

Defense Against LLM Backdoors using Critical Neuron Isolation Pruning

arXiv:2607.19894v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to backdoor attacks, where hidden triggers induce malicious outputs. Existing defenses generally fall into

Defer to Plan: Adaptive Multi-Agent Fusion for End-to-End V2X Driving

arXiv:2607.19774v1 Announce Type: new Abstract: Vehicle-to-everything-aided autonomous driving (V2X-AD) significantly enhances driving performance through information sharing. However, existing collab

agentsarxiv-cs-ro

Delineate Anything v2: A Global Foundation Model for Field Delineation

arXiv:2607.19069v1 Announce Type: new Abstract: Accurate agricultural field boundary delineation at large scale is a foundational task for food security, supply chain transparency, and carbon accounti

Directional Kernel Mean Difference: A Fast Signed Statistic for Univariate Distribution Comparison

arXiv:2607.20119v1 Announce Type: cross Abstract: We introduce the Directional Kernel Mean Difference (DKMD), a signed statistic for univariate distribution comparison that preserves the direction of

Distributed Optimization via Energy Conservation Laws in Dilated Coordinates

arXiv:2409.19279v2 Announce Type: replace-cross Abstract: Continuous-time models can reveal accelerated structures in distributed optimization, but their rates need not survive direct discretization.

DobicVLM: Aligning Chest X-Ray Report Generation with Clinically-Grounded Programmatic Rewards via Group Relative Policy Optimization

arXiv:2607.18988v1 Announce Type: new Abstract: Medical imaging is a cornerstone of diagnostics, yet automated chest X-ray report generation struggles with structural adherence, anatomical completenes

Dreamer-CPC: Message Learning with World Models for Decentralized Multi-agent Reinforcement Learning

arXiv:2607.19809v1 Announce Type: cross Abstract: In multi-agent reinforcement learning (MARL), inter-agent communication is effective for improving performance under partial observability. Representa

agentsarxiv-cs-lg

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

arXiv:2607.18958v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulne

Dynamical and Optimization Trade-offs of Levi--Civita Coordinates for Learned Close-Encounter Dynamics

arXiv:2607.20235v1 Announce Type: cross Abstract: Classical regularization removes the binary-collision singularity from the Kepler problem, but its value as a representation for learned Hamiltonian d

ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualization

arXiv:2607.18466v1 Announce Type: new Abstract: Recent advances in differentiable Gaussian splatting have highlighted the potential of primitive-based approaches as alternative scene representations f

EGRNet: A Lightweight Semantic Segmentation Network with Edge-Gated Refinement and Adversarial Sensing

arXiv:2607.19617v1 Announce Type: new Abstract: As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semant

End-to-End Differential Privacy in Training Deep Neural Network Classifiers

arXiv:2607.19580v1 Announce Type: new Abstract: Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from

Enhanced Neural Quantum State via Annealed Gradient Descent

arXiv:2607.18865v2 Announce Type: replace-cross Abstract: Neural quantum states offer expressive representations of quantum many-body wave functions, yet their practical accuracy can be limited by sto

ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models

arXiv:2607.20092v1 Announce Type: cross Abstract: Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is rele

Environment-free Synthetic Data Generation for API-Calling Agents

arXiv:2607.16900v2 Announce Type: replace Abstract: Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale

agentsarxiv-cs-ai

ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program

arXiv:2607.19947v1 Announce Type: new Abstract: Electronic Theater Programs (ETPs) serve as critical promotional media in the performing arts, comprising a multi-page collection of heterogeneous visua

Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean

arXiv:2607.19374v1 Announce Type: new Abstract: Recent formal reasoning systems have reached IMO-level performance, yet they leave a fragmented landscape: algebra and number theory are handled in Lean

EvoThink: Evolving Thinking in Large Reasoning Models via Self-Pruning and Aha-Moment Preference Optimization

arXiv:2607.19962v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) often suffer from overthinking due to redundant verification steps. Existing approaches for mitigating overthinking, such

Tutorials

Expert-Guided Forecast Editing for Time-Series Foundation Models

arXiv:2607.19659v1 Announce Type: new Abstract: Time-series foundation models can forecast across heterogeneous domains without task-specific training, but their forecasts are fixed once produced and

tutorialsarxiv-cs-lg

ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis

arXiv:2607.19341v1 Announce Type: new Abstract: Recent advances in multimodal generative models have enabled instruction-based image generation to move beyond semantic manipulation to knowledge-driven

FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images

arXiv:2607.18283v1 Announce Type: cross Abstract: Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnorm