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First Plan Then Evaluate: Multi-Target Planning with Post-Planning Success Evaluation Improves Learning-Based Grasping Pipelines

arXiv:2509.07162v2 Announce Type: replace Abstract: Autonomous multi-finger grasping is a fundamental capability in robotic manipulation. Optimization-based approaches show strong performance, but ten

agentsarxiv-cs-ro

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FirstResearch: Auditable Question Formation for LLM Scientific Discovery Agents

DGX agent

arXiv:2607.05682v1 Announce Type: new Abstract: LLM systems for scientific discovery increasingly assist with ideation, literature synthesis, experiment planning, and report generation, but the first

model-releasesarxiv-cs-ai

8 Jul 2026

FlexAct: Why Learn when you can Pick?

arXiv:2601.06441v2 Announce Type: replace Abstract: Learning activation functions has emerged as a promising direction in deep learning, allowing networks to adapt activation mechanisms to task-specif

tutorialsarxiv-cs-lg

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games

arXiv:2607.06514v1 Announce Type: new Abstract: We present FootsiesGym, an open-source environment for learning in a non-trivial two-player, zero-sum, imperfect-information game. Built on HiFight's mi

FORGE: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning

arXiv:2607.05780v1 Announce Type: cross Abstract: While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to nove

Foundation Models for Automatic CAD Generation

arXiv:2607.05573v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) and Vision-Language Models (VLMs) enable the automatic generation of parametric 3D designs from natural-

FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models

arXiv:2607.05711v1 Announce Type: cross Abstract: Diffusion models have become a dominant paradigm for high-quality generative modeling, while post-training is essential for adapting them to diverse d

FreqDepthKV: Frequency-Guided Depth Sharing for Robust KV Cache Compression in Long-Context LLM Inference

arXiv:2607.06519v1 Announce Type: new Abstract: Long-context LLM inference is increasingly limited by the memory and bandwidth cost of KV caches, yet aggressive compression can remove the layer-specif

Local Ai

Freqformer: Image-Demoireing Transformer via Effective Frequency Decomposition

arXiv:2505.19120v2 Announce Type: replace Abstract: Image demoireing remains a challenging task due to the complex interplay between texture corruption and color distortions caused by moire patterns.

local-aiarxiv-cs-cv

From Application-Layer Simulation to Native Meta-Architecture: Structural Tension as an Endogenous Driver for Heterogeneous AI Evolution

arXiv:2607.06269v1 Announce Type: new Abstract: Current large language models (LLMs) are fundamentally stateless: their behavior is fully determined by input at inference time, and any higher-order co

From Blueprint to Reality: Modeling and Applying Putnam's Social Capital Theory with LLM-based Multi-agent Simulations

arXiv:2607.06080v1 Announce Type: cross Abstract: Putnam's Social Capital Theory is a foundational framework for collective action and community prosperity. However, traditional empirical methods face

From Closed-Loop Optimization to Open Decision Making: Coupled Digital Twins for Predictive and Autonomous Microscopy

arXiv:2607.05758v1 Announce Type: cross Abstract: Automated experimentation is moving from closed-loop optimization toward open decision-making, where human or AI planners must forecast the consequenc

agentsarxiv-cs-lg

From Foundation to Application: Improving VLA Models in Practice

model-releasesarxiv-cs-ro

arXiv:2607.06403v1 Announce Type: new Abstract: Despite recent progress of VLA foundation models, the disparity between laboratory conditions and real-world applications continues to impede their prac

From Global to Granular: Revealing IQA Model Performance via Correlation Surface

arXiv:2601.21738v2 Announce Type: replace-cross Abstract: Evaluation of Image Quality Assessment (IQA) models has long been dominated by global correlation metrics, such as Pearson Linear Correlation

From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond

arXiv:2607.05563v1 Announce Type: new Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of

From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation

arXiv:2603.15600v2 Announce Type: replace-cross Abstract: Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video ML

From Passive Retrieval to Active Memory Navigation: Learning to Use Memory as a Structured Action Space

arXiv:2607.05794v1 Announce Type: new Abstract: Long-term user memory is essential for personalized conversational agents, yet many memory systems still expose memory through passive retrieval interfa

From Pixels to Portraits: A Comprehensive Survey of Talking Head Generation Techniques and Applications

arXiv:2308.16041v2 Announce Type: replace Abstract: Talking head generation has progressed rapidly from landmark- and GAN-based facial animation to diffusion models, neural rendering, 3D-aware avatars

safetyarxiv-cs-cv

From RGB Generation to Dense Field Readout: Pixel-Space Dense Prediction with Text-to-Image Models

arXiv:2607.06553v1 Announce Type: new Abstract: Large-scale text-to-image models are attractive backbones for dense prediction because RGB generation pretraining learns rich semantic, structural, and

researcharxiv-cs-cv

From Sinhala to Dhivehi: Cross-Lingual Transfer Learning for Low-Resource Speech Recognition

arXiv:2607.06289v1 Announce Type: new Abstract: Dhivehi, the national language of the Maldives, is currently under-resourced for automatic speech recognition (ASR) and other NLP tasks. This study inve

researcharxiv-cs-cl

From Textural Counterpoint to Feature Encoding: A Multi-Dimensional Machine Representation Study of Haydn's 'The Lark' Integrating Electroacoustic Analysis

arXiv:2607.05902v1 Announce Type: cross Abstract: Chamber music, as a highly precise multi-part interactive system, contains a logic of 'role assignment and dynamic interaction' that provides an extre

From Voting to Agent Collaboration: Answer-Type-Aware LLM Pipelines for BioASQ 14b

arXiv:2607.06452v1 Announce Type: cross Abstract: Biomedical question answering requires not only accurate extraction of information from scientific literature but also reliable integration of evidenc

agentsarxiv-cs-ai

Full-range Binary Classifier Calibration for Stable Model Updates in Production

arXiv:2607.05481v1 Announce Type: cross Abstract: Detection models running in adversarial environments face a malicious distribution that drifts rapidly while the benign distribution stays comparative

applicationsarxiv-cs-ai

FUSE: A Flow-based Mapping Between Shapes

arXiv:2511.13431v2 Announce Type: replace Abstract: We introduce a novel neural representation for maps between 3D shapes based on flow-matching models, which is computationally efficient and supports

researcharxiv-cs-cv

GaussFusion: Towards Multimodal 3D Gaussian Pretraining

arXiv:2607.05906v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represent

safetyarxiv-cs-cv

GEM-Occ: From Visual Geometry Evidence to Embodied Semantic Occupancy Memory

arXiv:2607.05543v1 Announce Type: cross Abstract: Semantic occupancy provides a structured spatial memory for embodied indoor agents by jointly representing occupied regions, observed free space, unkn

Generalized Synthetic Image Detection with Enhanced RGB-Noise Representation Learning

arXiv:2607.06354v1 Announce Type: new Abstract: The rapid advancement of large-scale generative models has accelerated the spread of highly deceptive AI-generated images, making generalized synthetic

Geometry-Aware Infrastructure-Anchored Denoiser for UWB Sensing and Work-Zone Reconstruction

arXiv:2607.05449v1 Announce Type: cross Abstract: Accurate work-zone geometry perception is critical for intelligent transportation systems, and ultra-wideband sensing offers a low-cost approach for i

applicationsarxiv-cs-ai

Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion

arXiv:2607.06546v1 Announce Type: cross Abstract: Denoising graphs is a fundamental problem in graph learning and the core operation of graph diffusion models. Attention-based architectures like graph

tutorialsarxiv-cs-ai

GraphAllocBench: A Flexible Benchmark for Preference-Conditioned Multi-Objective Policy Learning

model-releasesarxiv-cs-lg

arXiv:2601.20753v4 Announce Type: replace Abstract: Preference-Conditioned Policy Learning (PCPL) in Multi-Objective Reinforcement Learning (MORL) approximates diverse Pareto-optimal solutions by cond

GraphBU: MILP Instance Generation with Graph-Native Block Units

arXiv:2607.06532v1 Announce Type: new Abstract: Mixed-integer linear programming (MILP) instances used for solver development are hard to obtain when models come from private or application-specific p

researcharxiv-cs-lg

GraspIT: A Dataset Bridging the Sim-to-Real gap and back for Validated Grasping SE(3) Pose Generation

arXiv:2607.05869v1 Announce Type: cross Abstract: Robust robotic grasping of novel objects requires datasets that simultaneously provide photorealistic RGB-D observations, physically validated grasp q

safetyarxiv-cs-cv

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to

applicationsarxiv-cs-cv

Harnessing Code Agents for Automatic Software Verification

arXiv:2607.06341v1 Announce Type: cross Abstract: Formal verification offers the strongest guarantee of software correctness, but it does not scale: the proofs demanded by interactive theorem provers

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction

arXiv:2607.05568v1 Announce Type: cross Abstract: Representing 3D shapes as compact sets of geometric primitives is fundamental to robotics, simulation, and scene understanding. Generative image model

Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context

arXiv:2607.05880v1 Announce Type: cross Abstract: Imaging demand is growing faster than the radiology workforce can expand, and reporting backlogs cannot be resolved through training and recruitment a

Heckman-Corrected Epistemic Uncertainty: Selection on Unobservables Defeats Importance Weighting

arXiv:2607.05806v1 Announce Type: new Abstract: Training data for machine learning is routinely collected by a selection process the model never sees: loans are observed only when granted, outcomes on

safetyarxiv-cs-lg

HERB: Human-augmented Efficient Reinforcement learning for Bin-packing

arXiv:2504.16595v2 Announce Type: replace-cross Abstract: Packing objects efficiently is a fundamental problem in logistics, warehouse automation, and robotics. When dealing with highly diverse 3D obj

applicationsarxiv-cs-lg

Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLMs

model-releasesarxiv-cs-cl

arXiv:2607.06540v1 Announce Type: new Abstract: Developing seamless, high-performance, native intelligent full-duplex Spoken Language Models (SLMs) remains a critical challenge and long-standing goal

Hierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)

arXiv:2607.05585v1 Announce Type: cross Abstract: FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosi

Local Ai

High-Resolution Artwork Outpainting with Global Blueprint Guidance and Layout Control

arXiv:2607.06162v1 Announce Type: new Abstract: Image outpainting extends an image beyond its original borders, requiring seamless style integration and globally coherent scene completion. Building on

local-aiarxiv-cs-cv

Local Ai

Higher-Order Certified Robustness for Regression

arXiv:2607.05536v1 Announce Type: cross Abstract: Randomized smoothing has emerged as a scalable technique for certifying the adversarial robustness of classifiers. However, its application to regress

local-aiarxiv-cs-lg

Hilti-Trimble-Oxford Dataset: 360 Visual-Inertial Benchmark with Floor Plan Priors for SLAM and Localization

model-releasesarxiv-cs-ro

arXiv:2607.06464v1 Announce Type: new Abstract: Automated progress monitoring on construction sites is an active area of research and development. Robot and human-carried mapping systems have been dev

Hardware

HJCD-IK: GPU-Accelerated Inverse Kinematics through Batched Hybrid Jacobian Coordinate Descent

arXiv:2510.07514v2 Announce Type: replace Abstract: Inverse Kinematics (IK) is a core problem in robotics, in which joint configurations are found to achieve a (collision-free) desired end-effector po

hardwarearxiv-cs-ro

HoloCount: A Holistic Visual Counting Benchmark for MLLMs

arXiv:2607.06420v1 Announce Type: new Abstract: Visual counting is a fundamental pillar of multimodal intelligence, requiring a seamless integration of fine-grained grounding and spatial reasoning. Wh

How Can Mamba Learn In Context with Outliers and Generalize Provably?

arXiv:2510.00399v2 Announce Type: replace Abstract: The Mamba model has gained significant attention for its computational advantages over Transformer-based models, while achieving comparable performa

tutorialsarxiv-cs-lg

How Personas Can Influence Agents to Play Split or Steal

arXiv:2607.05398v1 Announce Type: new Abstract: Personas are often employed to guide large language model agents, yet their effectiveness in shaping strategic behavior in social dilemma settings remai

tutorialsarxiv-cs-cl

Hypothesis-driven Model Expansion under Uncertainty for Open-World Robot Planning

arXiv:2607.06501v1 Announce Type: new Abstract: We consider an open-world planning setting in which service robots must operate in unknown environments with incomplete knowledge of objects and actions

agentsarxiv-cs-ro