Search: “framework”

The Three Dimensions of ROS 2 Middleware

arXiv:2607.01304v1 Announce Type: new Abstract: ROS 2 (Robot Operating System 2) has emerged as the de facto standard for modern robot software development, with middleware implementations such as the

researcharxiv-cs-ro

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment

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DGX agent

arXiv:2511.05150v2 Announce Type: replace-cross Abstract: Molecular biomarker testing in pathology is often costly and tissue-consuming, limiting scalable clinical deployment. Artificial intelligence

researcharxiv-cs-ai

3 Jul 2026

Transformer Geometry Observatory TGO-II: Representational Similarity Observatory

arXiv:2607.02386v1 Announce Type: cross Abstract: While Vision Transformers have achieved remarkable success across computer vision and language applications, the geometric evolution of their internal

safetyarxiv-cs-lg

VaSST: Variational Inference for Symbolic Regression using Soft Symbolic Trees

arXiv:2602.23561v2 Announce Type: replace-cross Abstract: Symbolic regression (SR) has gained recent traction in AI-driven scientific discovery for learning closed-form physical laws. Yet existing met

Verifiable Knowledge Expansion through Retrieval-Grounded Formal Concept Analysis

arXiv:2607.01773v1 Announce Type: new Abstract: Ontology construction requires deciding which objects, attributes, and structural relations should be accepted as valid knowledge. Language models can p

Tutorials

Visually Grounded Self-Reflection for Vision-Language Models via Reinforcement Learning

arXiv:2607.02490v1 Announce Type: new Abstract: Large vision-language models can reason over multimodal inputs by generating textual chains of thought (CoT). A key capability exhibited in CoT reasonin

tutorialsarxiv-cs-cl

Local Ai

VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon

arXiv:2607.01804v1 Announce Type: new Abstract: Vision-Language-Action (VLA) foundation models have recently achieved strong progress in embodied intelligence. To reduce policy-call frequency while pr

local-aiarxiv-cs-ro

Local Ai

VT-WAM: Visual-Tactile World Action Model for Contact-Rich Manipulation

arXiv:2607.02503v1 Announce Type: new Abstract: Contact-rich manipulation requires policies to react to local deformation, pressure, slip, and friction, yet these cues are temporally sparse and often

local-aiarxiv-cs-ro

WARP: Weight-Space Analysis for Recovering Training Data Portfolios

model-releasesarxiv-cs-lg

arXiv:2607.01686v1 Announce Type: new Abstract: Foundation models are routinely released to the public, yet the data recipes used to train them -- such as domain mixture weights that determine how dif

Local Ai

Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

arXiv:2511.10687v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled w

local-aiarxiv-cs-ai

World Wide Models: Literary Tools for Cultural AI

arXiv:2607.02369v1 Announce Type: cross Abstract: LLMs stage a new form of cultural encounter that is massive, automated, and monolingual. Literary disciplines have always negotiated cultural struggle

WorldSample: Closed-loop Real-robot RL with World Modelling

arXiv:2607.02431v1 Announce Type: cross Abstract: Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis

arXiv:2607.01918v1 Announce Type: new Abstract: We present Zeus, a unified tuning-free Time Series Foundation Model (TSFM) that delivers superior performance across diverse analysis tasks without any

A Category Theory Account of AI Identity

arXiv:2607.00220v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are routinely modified after deployment through retraining and changes in their environments. These transformatio

Agents

A Task-State Representation for Long-Horizon Mobile GUI Agents

arXiv:2607.00502v1 Announce Type: new Abstract: While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient

agentsarxiv-cs-cl

Hardware

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling

arXiv:2607.00773v1 Announce Type: new Abstract: Discrete diffusion models are widely used for learning and generating discrete distributions. As the generation process is inherently sequential, the ac

hardwarearxiv-cs-lg

Active View Selection with Perturbed Gaussian Ensemble for Tomographic Reconstruction

arXiv:2603.06852v2 Announce Type: replace Abstract: Sparse-view computed tomography (CT) is critical for reducing radiation exposure to patients. Recent advances in radiative 3D Gaussian Splatting (3D

AdaBoosting Text Prompts for Vision-Language Models

arXiv:2607.00684v1 Announce Type: new Abstract: The classification accuracy of pretrained Vision-Language Models (VLMs) relies on the quality of the text prompts. Handcrafted templates and Large Langu

Adversarial Pragmatics for AI Safety Evaluation: A Benchmark for Instruction Conflict, Embedded Commands, and Policy Ambiguity

arXiv:2607.01153v1 Announce Type: cross Abstract: Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: whether a model has followed an in

AFFMAE: Scalable Vision Pre-Training for High-Resolution Microscopy Segmentation on Desktop Hardware

model-releasesarxiv-cs-cv

arXiv:2602.16249v2 Announce Type: replace Abstract: Self-supervised pretraining has transformed computer vision by enabling data-efficient fine-tuning, yet high-resolution pretraining typically requir

Affogato: Open-Vocabulary Affordance Grounding with Automated Data Generation at Scale

arXiv:2506.12009v2 Announce Type: replace Abstract: Affordance grounding aims to localize where to interact with an object, a fundamental capability for embodied agents. Yet progress is bottlenecked b

Agents

Agentic generation of verifiable rules for deterministic, self-expanding reaction classification

arXiv:2607.01061v1 Announce Type: new Abstract: Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transfo

agentsarxiv-cs-ai

ALEE: Any-Language Evaluation of Embeddings via English-Centric Minimal Pairs

arXiv:2607.00171v1 Announce Type: new Abstract: Text embeddings are standard for semantic similarity tasks, yet their evaluation remains an open challenge. Current benchmarks are static, cover only a

researcharxiv-cs-cl

AlgoBench: Benchmarking Algorithmic Adaptation in Code Generation

arXiv:2607.00062v1 Announce Type: cross Abstract: High pass rates on established programming benchmarks such as HumanEval and LiveCodeBench do not always show whether a model can reason about algorith

ATM: CID-Brokered Pre-Write Admission for Multi-Agent Code Co-Synthesis

arXiv:2607.00041v1 Announce Type: cross Abstract: Multi-agent LLM systems can decompose software-engineering work into planning, generation, validation, and repair, but a narrower systems problem rema

AutoMem: Automated Learning of Memory as a Cognitive Skill

arXiv:2607.01224v1 Announce Type: new Abstract: Memory expertise is a learned skill: knowing what to encode, when to retrieve, and how to organize knowledge--a capacity known in cognitive science as m

Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering

arXiv:2607.00972v1 Announce Type: new Abstract: Trustworthy deployment of Agentic Retrieval-Augmented Generation (RAG) systems requires mechanisms for estimating when multi-stage reasoning pipelines m

Beyond Activation Alignment:The Alignment-Diversity Tradeoff in Task-Aware LLM Quantization

model-releasesarxiv-cs-lg

arXiv:2607.00908v1 Announce Type: new Abstract: Mixed-precision quantization (MPQ) has become a key technique for deploying large language models under stringent memory and compute constraints. We fir

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces

arXiv:2607.00481v1 Announce Type: cross Abstract: Jailbreak attacks remain a critical threat to the safe deployment of large language models (LLMs). While prior work has primarily studied attacks and

Caption Bottleneck Models

arXiv:2607.00578v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide interpretability by routing predictions through a layer of human-understandable concepts. However, defining an

safetyarxiv-cs-cv

CAT: Confidence-Adaptive Thinking for Efficient Reasoning of Large Reasoning Models

arXiv:2607.00862v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable success on complex tasks by leveraging long chain-of-thought (CoT) trajectories, yet they frequ

ClinRAG-GRAPH: Clinical-prior Retrieval-Augmented Graph Model with Domain Adversarial Learning for Breast pCR Prediction

arXiv:2607.00798v1 Announce Type: new Abstract: Neoadjuvant chemotherapy (NAC) response prediction is clinically important for treatment stratification in breast cancer. However, robust pre-treatment

safetyarxiv-cs-cv

Hardware

Condensing Large-Scale Datasets Directly with Minimal Information Loss

arXiv:2607.00916v1 Announce Type: new Abstract: Recent advancements in scaling dataset distillation rely heavily on decoupled information extraction pipelines, comprising SQUEEZE, RECOVER, and RELABEL

hardwarearxiv-cs-cv

Applications

Constrained Bayesian Optimisation with Multiple Information Sources

arXiv:2607.00865v1 Announce Type: new Abstract: Bayesian Optimisation (BO) under unknown constraints is particularly challenging when feasible regions are small. In such settings, existing methods tha

applicationsarxiv-cs-lg

Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction

arXiv:2607.00001v1 Announce Type: new Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized. This assumption conflicts with extensive empirica

Controllable Narrative Rendering for Enhanced Assisted Writing

arXiv:2607.00009v1 Announce Type: cross Abstract: Despite the remarkable proficiency of large language models (LLMs) in basic writing assistance, their utility in creative writing is fundamentally hin

Tutorials

CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wild

arXiv:2607.00321v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D models of highly articulated animals, such as dogs, from a single in-the-wild image remains a formidable challenge. In t

tutorialsarxiv-cs-cv

CPDDNet: Color-Polarization Denoising and Demosaicking Network

model-releasesarxiv-cs-cv

arXiv:2607.01100v1 Announce Type: new Abstract: Color-polarization imaging using a color-polarization filter array (CPFA) sensor captures both texture (color intensity) and physical (polarization) inf

Tutorials

Decision-focused Sparse Tangent Portfolio Optimization

arXiv:2607.00581v1 Announce Type: new Abstract: Sparse tangent portfolio optimization aims to learn an interpretable, low-cardinality portfolio in the tangency direction of the mean-variance frontier.

tutorialsarxiv-cs-lg

Decoupled Guidance: Disentangling Subject and Context Pathways in Text-to-Image Personalization

arXiv:2607.00766v1 Announce Type: new Abstract: Text-to-image personalization aims to generate a user-provided subject in novel scenes described by text. However, most existing methods encode subject

Deep Learning-Driven Black-Box Doherty Power Amplifier with Pixelated Output Combiner and Extended Efficiency Range

arXiv:2603.16565v2 Announce Type: replace-cross Abstract: This article presents a deep learning-driven inverse design methodology for Doherty power amplifiers (PA) with multi-port pixelated output com

Distill to Detect: Exposing Stealth Biases in LLMs through Cartridge Distillation

arXiv:2607.01208v1 Announce Type: cross Abstract: Language models deployed in high-stakes roles can potentially favor certain entities, brands, or viewpoints, steering user decisions at scale. Such pr

Distributed Online Bandit Submodular Maximization with Bounded Sampling Violations

arXiv:2607.00680v1 Announce Type: new Abstract: We study distributed online submodular maximization under partition matroid constraints, in which multiple agents select a limited number of actions fro

Does Your ViT Still Need U-Net for Segmentation?

model-releasesarxiv-cs-cv

arXiv:2607.00223v1 Announce Type: new Abstract: Medical image segmentation is dominated by U-Net-style encoder-decoder architectures. Vision Transformers (ViTs) overcome the limited receptive field of

DroneIQA-VLE: Multi-Task Drone Image Quality Assessment via Vision-Language Ensemble

arXiv:2607.00416v1 Announce Type: new Abstract: We present DroneIQA-VLE, our solution to the ICME 2026 Drone-IQA Grand Challenge on Target-aware Image Quality Assessment for Low-altitude UAV Images. T

Efficient Multilingual Reasoning Transfer via Progressive Code-Switching

arXiv:2607.00485v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong reasoning capabilities in English, yet their performance degrades significantly when required to reas

researcharxiv-cs-cl

ELMP: Efficient Learning for Motion Planning via Analytical Policy Gradients

arXiv:2607.00215v1 Announce Type: new Abstract: Neural Motion Planners (NMPs) enable fast reactive motion generation, but adapting them to new environments typically requires recollecting large expert

safetyarxiv-cs-ro

EmbodimentSemantic: A Spatial Scene-Graph Dataset and Benchmark for Vision-Language Models on Embodied Manipulation Trajectories

model-releasesarxiv-cs-ro

arXiv:2607.00020v1 Announce Type: new Abstract: Spatial grounding remains a key limitation of vision-language-action (VLA) systems for robotic manipulation. While current models can recognize objects