Search: “engineering”

ArtisanCAD: An Industrial-Level CAD Agent with Expert-Grounded Knowledge Distillation

arXiv:2607.05750v1 Announce Type: new Abstract: Computer-aided design (CAD) for industrial components requires long-horizon procedural modeling, robust feature dependencies, editable parametric geomet

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation

DGX agent

arXiv:2607.05985v1 Announce Type: new Abstract: This paper presents a black-box evaluation framework to systematically assess the ability of Large Language Models (LLMs) to generate Design Structure M

model-releasesarxiv-cs-ai

8 Jul 2026

Beyond Refusal: A Same-Lineage Study of Aligned and Abliterated LLMs for Vulnerability Analysis

arXiv:2607.05842v1 Announce Type: cross Abstract: Large language model (LLM)-assisted software security operates at a difficult boundary: the vulnerability-analysis terminology needed for legitimate c

CSTutorBench: Benchmarking Small Language Models as Tutors for Block-Based Programming

arXiv:2607.05571v1 Announce Type: new Abstract: Large language models are increasingly explored as AI tutors, yet deploying them in K-12 settings raises concerns around privacy, cost, and reliance on

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-

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

Image2Sim: Scaling Embodied Navigation via Generative Neural Simulator

arXiv:2607.05765v1 Announce Type: new Abstract: Embodied navigation aims to build agents that interpret multimodal goals, reason in 3D space, and reach target destinations reliably in the real world.

applicationsarxiv-cs-cv

MoWorld: A Flash World Model

arXiv:2607.06216v1 Announce Type: new Abstract: The future of World Models depends not only on scaling model capability, but also on scaling practicality and inference efficiency. High-frame-rate infe

agentsarxiv-cs-cv

Onnes: A Physics-Grounded Multi-Agent LLM Simulator for Cryogenic Fault Diagnosis in Quantum Computing Infrastructure

arXiv:2607.05805v1 Announce Type: new Abstract: Dilution refrigerators are the enabling infrastructure of superconducting quantum computers, yet their fault diagnosis is still dominated by threshold a

Prompting Complexity: Shortest Prompts for Texts and Behaviors in LLMs

arXiv:2607.06145v1 Announce Type: new Abstract: In this paper, we define the quantity of prompting complexity: for a fixed instruction-tuned language model, what is the shortest plausible prompt that

researcharxiv-cs-cl

Hardware

RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation

arXiv:2607.06558v1 Announce Type: new Abstract: Scaling robot learning requires massive, diverse trajectory data, yet collection is currently bottlenecked by physical teleoperation, where every demons

hardwarearxiv-cs-ro

Scene Graph Thinking: Reinforcing Structured Visual Reasoning for Multimodal Large Language Models

arXiv:2607.05716v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong perception and reasoning capabilities. However, most existing models focus on isolated

researcharxiv-cs-cv

Scientific Code Search at Scale: A Multi-Domain Dataset and Benchmark

arXiv:2607.05443v1 Announce Type: cross Abstract: Scientists increasingly rely on open-source tools to support their research workflows, yet discovering relevant software among over 600 million GitHub

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines cons

SplineNet: An Isogeometric Deep Learning Method for Complex Shells

arXiv:2607.06026v1 Announce Type: new Abstract: We present a novel isogeometric deep learning method, termed SplineNet, for the seamless design and analysis of shell structures with complex geometries

applicationsarxiv-cs-lg

Statistically Meaningful Geometry and Gauge Symmetry Breaking: A Geometric Foundation for Scientific Discovery and Intelligence Emergence

model-releasesarxiv-cs-lg

arXiv:2607.05436v1 Announce Type: new Abstract: The rapid scaling of over-parameterized machine learning architectures, particularly LLMs, raises a profound crisis: do these systems exhibit genuine in

Structured Data Extraction from Real Estate Documents using Clustering, Classification, and Large Language Models

model-releasesarxiv-cs-cv

arXiv:2607.06012v1 Announce Type: new Abstract: Real estate property listings expose structured metadata through the API. Still, the richest property-level information (i.e., legal status, structural

What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests

arXiv:2607.05666v1 Announce Type: cross Abstract: AI coding agents are black boxes: we cannot inspect how they generate code, but we can inspect what they change. This distinction matters for search-b

A Near-Linear-Time Solver for Graph p-Laplacian Semi-Supervised Learning via Continuation in p

model-releasesarxiv-cs-lg

arXiv:2607.03503v1 Announce Type: new Abstract: Graph-based semi-supervised learning (SSL) propagates a few labels over a similarity graph by minimizing a Dirichlet-type energy. The standard quadratic

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel

Agentic Retrieval-Augmented Generation for Financial Document Question Answering

arXiv:2605.05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual na

AGL-1: The Enterprise AI Governance Layer as a Control Plane for Trusted Enterprise Intelligence

arXiv:2607.03516v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generati

ChainReaction: Causal Chain-Guided Reasoning for Modular and Explainable Causal-Why Video Question Answering

arXiv:2508.21010v3 Announce Type: replace-cross Abstract: Existing Causal-Why Video Question Answering (VideoQA) models often struggle with higher-order reasoning, relying on opaque, monolithic pipeli

researcharxiv-cs-ai

Compressed Computation under L^4 Loss is likely Computation in Superposition

arXiv:2607.04800v1 Announce Type: new Abstract: Neural networks are thought to represent concepts as directions in their activation space, and superposition lets them encode more concepts than they ha

researcharxiv-cs-lg

Local Ai

CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning

arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio

local-aiarxiv-cs-cv

Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation

arXiv:2607.05377v1 Announce Type: cross Abstract: While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to th

DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation

arXiv:2607.05147v1 Announce Type: new Abstract: Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel dra

EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments

arXiv:2607.05155v1 Announce Type: new Abstract: Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deploy

agentsarxiv-cs-cl

EEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection

arXiv:2607.04558v1 Announce Type: cross Abstract: Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing de

Efficient Discovery of Conditional Dependencies with Desbordante

arXiv:2607.04030v1 Announce Type: cross Abstract: Conditional functional dependencies (CFDs) are functional dependencies with a restricted scope: they specify the context in which a dependency holds a

researcharxiv-cs-ai

Tutorials

Empirical Computation: Prompting versus Programming

arXiv:2503.10954v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents can solve *any* computational problem *without* an algorithm in a runtime *independent* of the computational

tutorialsarxiv-cs-ai

EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer

arXiv:2607.05202v1 Announce Type: new Abstract: Agent self-evolution in long-horizon LLM systems is largely procedural: useful experience is not merely stored information, but reusable procedures for

Tutorials

EvoOtter: Evolutionary Reproduction Test Generator

arXiv:2607.02854v1 Announce Type: cross Abstract: Before fixing an issue, it is useful to first reproduce it by generating a bug reproduction test (BRT). However, generating a BRT is itself a challeng

tutorialsarxiv-cs-lg

Explainable Reinforcement Learning for Adaptive Traffic Signal Control

arXiv:2607.03703v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traf

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline

arXiv:2607.04448v1 Announce Type: cross Abstract: Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) po

Local Ai

Graph Neural Networks are Heuristics

arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to

local-aiarxiv-cs-ai

Heaviside Continuity of Rolling Coefficients for Eliminating Epistemic Entropy in Large Language Models

arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro

Holo-Captioning: Toward the Text Equivalent of 3D Scenes

model-releasesarxiv-cs-cv

arXiv:2607.02908v1 Announce Type: new Abstract: This work introduces holo-captioning, a novel task that strives to seek the text equivalent of 3D scenes. As the initial step, we formulate holo-caption

Individual Parameters in Weight-Sparse Transformers Appear Interpretable

arXiv:2607.02964v1 Announce Type: cross Abstract: A central goal of mechanistic interpretability is to understand how neural networks work and what each individual component does. Dominant circuit-fin

researcharxiv-cs-ai

IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation

model-releasesarxiv-cs-cv

arXiv:2512.10730v2 Announce Type: replace Abstract: Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowled

IRIS: An Intelligent Vision-Language System for Ocular Surface Diseases via Topic Tree and Scene-Driven VQA Generation

arXiv:2607.04344v1 Announce Type: cross Abstract: While Large Vision-Language Models (VLMs) demonstrate remarkable generic capabilities, their clinical reasoning in specialized domains like ocular sur

karl. -- A Research Vehicle for Automated and Connected Driving

arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel

applicationsarxiv-cs-ro

LLMoxie: Exploring Agentic AI for Scientific Software Development

arXiv:2607.02703v1 Announce Type: cross Abstract: In this paper, we describe LLMoxie, an institutional AI platform whose three-tiered architecture supports multi-cloud and on-premise inference, a Lite

Memory-Efficient FastText: A Comprehensive Approach Using Double-Array Trie Structures and Mark-Compact Memory Management

model-releasesarxiv-cs-cl

arXiv:2506.01254v2 Announce Type: replace Abstract: FastText remains a practical choice for industrial word representation because it can synthesize vectors for out-of-vocabulary words from character

Local Ai

Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture

arXiv:2607.04391v1 Announce Type: new Abstract: Long-term memory remains a structural weakness of AI agents. The dominant approach, retrieval-augmented generation (RAG), relies on embedding-based simi

local-aiarxiv-cs-cl

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du

applicationsarxiv-cs-ai

NKI-Agent: Domain-Specific Fine-Tuning and Agentic Tool Use for Neuron Kernel Generation

model-releasesarxiv-cs-lg

arXiv:2607.04395v1 Announce Type: new Abstract: Recent agentic approaches to LLM-based kernel generation have achieved impressive results on CUDA. For emerging AI accelerators such as AWS Trainium and