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arXiv:2608.03689v1 Announce Type: new Abstract: Large language models are increasingly capable of synthesizing executable frontend projects, yet existing benchmarks still treat web generation as a sta

agentsarxiv-cs-ai

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LoCA: Forward-Only LLM Tuning after One-Shot Calibration with Local Credit Assignment

DGX agent

arXiv:2608.03020v1 Announce Type: new Abstract: Parameter-efficient post-training reduces the number of trainable parameters, but still requires repeated end-to-end backpropagation through the frozen

model-releasesarxiv-cs-ai

5 Aug 2026

Measurement Without Validity: The Compounding Reliability Problem in Agentic AI Evaluation

model-releasesarxiv-cs-ai

arXiv:2608.00794v2 Announce Type: replace Abstract: Agentic AI evaluation pipelines produce benchmark scores that justify deployment decisions, safety certifications, and regulatory compliance claims.

Measuring Explainer Stability via Attribution Separability

arXiv:2608.02697v1 Announce Type: cross Abstract: Attribution methods (AMs) assign an importance score to each feature and are widely adopted to explain black-box models. However, most methods can pro

tutorialsarxiv-cs-ai

MIMIC-MJX: Neuromechanical Emulation of Animal Behavior

arXiv:2511.20532v3 Announce Type: replace-cross Abstract: The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavi

tutorialsarxiv-cs-ai

Multi-Camera Trajectory Forecasting with Trajectory Tensors

arXiv:2108.04694v2 Announce Type: cross Abstract: We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network o

researcharxiv-cs-ai

PACE: Adaptive Budget Allocation for Time-Efficient Embodied Planning

model-releasesarxiv-cs-ai

arXiv:2608.03034v1 Announce Type: cross Abstract: Reasoning-enhanced large language models have achieved remarkable improvements in planning tasks, yet their deployment in embodied systems remains imp

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs

arXiv:2608.04010v1 Announce Type: cross Abstract: Existing scaling strategies for Multimodal Large Language Models (MLLMs) typically expand either model parameters or sequential inference computation,

PULSE: An Executable Contract Language for Spatiotemporal Knowledge Graph Engineering

arXiv:2608.02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose co

safetyarxiv-cs-ai

Local Ai

SAGE: Semantic Explainability of Attention-Based Survival Models in Computational Pathology

arXiv:2608.02803v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) is the predominant approach for slide-level prediction in computational pathology, yet its attentio

local-aiarxiv-cs-ai

Schedule-Informed Temporal Fusion Forecasting of Hourly Airport Security-Checkpoint Throughput

arXiv:2608.02950v1 Announce Type: new Abstract: Checkpoint staffing requires accurate forecasts of when screening demand will occur, yet flight schedules record departure times rather than passenger a

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

arXiv:2608.03250v1 Announce Type: cross Abstract: The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting i

Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

arXiv:2608.02811v1 Announce Type: new Abstract: Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty

safetyarxiv-cs-ro

The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems

arXiv:2608.03214v1 Announce Type: new Abstract: Large language models have transformed artificial intelligence from isolated prediction services into components of long-running, distributed systems th

safetyarxiv-cs-ai

Agents

TraceCAD: Trace-Guided Repair for Agentic CAD Generation

arXiv:2608.03062v1 Announce Type: new Abstract: LLM-based CAD agents produce executable parametric programs, but their correction loops may lose evidence about satisfied requirements, faulty operation

agentsarxiv-cs-ai

UniNav: A Unified World-Action Diffusion Model for Visual Navigation

model-releasesarxiv-cs-ai

arXiv:2608.03244v1 Announce Type: new Abstract: Image-goal visual navigation is a fundamental capability for embodied agents. Existing navigation policies efficiently predict waypoint trajectories but

Unsupervised Adversarial Domain Adaptation for Uterine layer Segmentation: From Labeled Cine to Unlabeled Dynamic EPI MRI

arXiv:2608.03762v1 Announce Type: cross Abstract: Uterine peristalsis is a key physiological phenomenon responsible for various functions across the menstrual cycle, intimately linked to uterine wall

researcharxiv-cs-cv

What is the Right Embedding Space for Contrastive Learning in REC?

arXiv:2505.22850v2 Announce Type: replace Abstract: Referring Expression Counting (REC) requires distinguishing visually similar objects described by fine-grained text cues. Existing methods tackle th

safetyarxiv-cs-cv

Where Knowledge Collides: A Mechanistic Study of Intra-Memory Knowledge Conflict in Language Models

arXiv:2601.09445v2 Announce Type: replace-cross Abstract: In language models (LMs), intra-memory knowledge conflict arises when inconsistent information about the same subject is encoded within the mo

applicationsarxiv-cs-ai

A Triple-Robustness Analysis of Retrieval-Augmented Generation for Multi-Hop Requirements Traceability

arXiv:2608.00705v1 Announce Type: cross Abstract: Reported verdicts on GraphRAG versus vector RAG disagree, and the evidence is typically tied to a single corpus, embedder, and judge -- and, we show,

Action-grounded tissue affordance enables anticipatory auto-framing that lowers surgeon cognitive workload during laparoscopic surgery

arXiv:2608.02471v1 Announce Type: new Abstract: Computational attention models could help surgeons manage the visual demands of laparoscopy, but they require dense spatial labels that are difficult to

applicationsarxiv-cs-cv

Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics

model-releasesarxiv-cs-lg

arXiv:2608.00850v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a versatile approach for solving nonlinear partial differential equations (PDEs), yet achieving

Automatic LV Localization and Short-Axis Plane Estimation from Arbitrary CMR Slice

model-releasesarxiv-cs-cv

arXiv:2608.00145v1 Announce Type: cross Abstract: Accurate estimation of left ventricular (LV) orientation is essential for cardiac magnetic resonance (CMR) imaging and downstream analysis. Existing m

Beyond Lanes: Traffic Flow Dynamics in Disordered Conditions Based on High-Resolution Trajectory Data

arXiv:2608.00602v1 Announce Type: cross Abstract: Disordered traffic flow is characterized by weak or non-existent lane discipline in the presence of strong vehicle heterogeneity and continuous latera

Breaking the Statistical Similarity Trap in Extreme Convection Detection

arXiv:2509.09195v2 Announce Type: replace-cross Abstract: Current evaluation metrics for deep learning weather models create a 'Statistical Similarity Trap', rewarding blurry predictions while missing

safetyarxiv-cs-cv

CLEAR: Conflict-aware Learning via Evidence-guided Adaptive Routing for Unified Sparse-View 3D Gaussian Super-Resolution

arXiv:2608.02206v1 Announce Type: new Abstract: Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and h

applicationsarxiv-cs-cv

Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization

model-releasesarxiv-cs-lg

arXiv:2608.01426v1 Announce Type: new Abstract: Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performan

Cross-Domain Hybrid OPD for Generalizable Search Agents

arXiv:2608.02101v1 Announce Type: new Abstract: Recent advances in Reinforcement Learning (RL) have substantially improved the capabilities of autonomous search agents, enabling sophisticated planning

safetyarxiv-cs-cl

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys

arXiv:2601.15307v2 Announce Type: replace-cross Abstract: The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to e

Agents

DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents

arXiv:2608.01827v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have advanced visual understanding and reasoning, yet their static parametric knowledge limits their ability to

agentsarxiv-cs-cv

DiffuseAgent-MI: Distributionally-Grounded,Tool-Integrated Self-Evolving Agents for Faithful Visual Reasoning

arXiv:2608.00540v1 Announce Type: new Abstract: Tool-integrated vision-language agents have made remarkable progress on compositional and multi-step visual reasoning. Yet their outputs frequently exhi

safetyarxiv-cs-cv

Diffusion-Based Body Schema Learning Enabling Abnormal-State Adaptation in Musculoskeletal Robots

arXiv:2608.01029v1 Announce Type: new Abstract: Musculoskeletal robots require an internal body schema that remains consistent under a wide range of physical state changes, including abnormalities suc

tutorialsarxiv-cs-ro

Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs

model-releasesarxiv-cs-cv

arXiv:2608.02396v1 Announce Type: new Abstract: Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural network

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

DPL: Depth-only Perceptive Humanoid Locomotion via Realistic Depth Synthesis and Cross-Attention Terrain Reconstruction

arXiv:2510.07152v3 Announce Type: replace Abstract: Recent advancements in legged robot perceptive locomotion have shown promising progress. However, terrain-aware humanoid locomotion remains largely

safetyarxiv-cs-ro

Local Ai

Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

arXiv:2409.05885v2 Announce Type: replace Abstract: Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehens

local-aiarxiv-cs-lg

Eigenvalues as a Metric for Memory Dynamics in Sequence Models

arXiv:2510.09379v2 Announce Type: replace Abstract: While softmax attention drives state-of-the-art performance in sequence modeling, its quadratic complexity motivates linear alternatives such as sta

Entity-Faithful Repair of Synthetic Supervision for Zero-Shot Image Captioning

arXiv:2608.00994v1 Announce Type: cross Abstract: Zero-shot image captioning aims to generate image descriptions without annotated image-text pairs. Recent approaches exploit text-to-image models to s

tutorialsarxiv-cs-cl

Fairness in Augmented Graph Learning: A Survey

arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat

safetyarxiv-cs-lg

From fragmented data to actionable design: Physics-calibrated learning for plastic upcycling

arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco

G-Skin: Learning to Bind 3D Gaussians with Generative Visual Priors

arXiv:2608.01726v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in photorealistic and efficient rendering, leading to a rapid increase in 3D assets represented by

researcharxiv-cs-cv

Gaokerena: A Small Persian Medical Language Model Family

arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused

Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI

model-releasesarxiv-cs-lg

arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

Heterogeneous Multi-Agent Reinforcement Learning for Radio Resource Management under Coupled Finite-Horizon Constraints

arXiv:2608.01745v1 Announce Type: new Abstract: Maximizing throughput under proportional fairness in dense wireless networks requires jointly managing user association, scheduling, base station (BS) a

safetyarxiv-cs-lg

Hybrid-Field Sparse Channel Representation and Recovery for XL-RIS-Assisted mmWave MIMO Systems

arXiv:2608.00052v1 Announce Type: cross Abstract: Extremely large-scale reconfigurable intelligent surface (XL-RIS)-assisted communication is regarded as a key enabling technology for future 6G networ

Inference-Time Policy Alignment for Fair Reinforcement Learning

arXiv:2608.00175v1 Announce Type: new Abstract: Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these

safetyarxiv-cs-lg

ISRS-DETR: Detection-Guided Click Propagation for Remote Sensing Interactive Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.02468v1 Announce Type: new Abstract: Interactive segmentation reduces the prohibitive cost of pixel-level annotation by allowing users to delineate objects with a few clicks. However, apply