Search: “engineering”

arXiv:2606.31946v1 Announce Type: new Abstract: The fundamental obstacle to industrial grade video generation is the lack of controllability: existing models treat video as a pixel distribution sampli

tutorialsarxiv-cs-cv

1 Jul 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Hardware

A Trainable-by-Parts Operator Learning Framework: Bridging DeepONet and Karhunen-Loeve Expansions for Large-Scale Applications

DGX agent

arXiv:2606.28519v1 Announce Type: new Abstract: Training operator-learning models for large-scale problems governed by partial differential equations (PDEs) is challenging due to the curse of dimensio

hardwarearxiv-cs-lg

30 Jun 2026

Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction

arXiv:2606.29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets. The model incorporates a Market R

ADEPT: An Entropy-Driven Dual-Strategy Agent for Interactive Video Retrieval

arXiv:2606.28326v1 Announce Type: cross Abstract: This research aims to solve the challenge of video retrieval from massive datasets, caused by ambiguous user queries. Prevailing single-round retrieva

Agentic Abstention: Do Agents Know When to Stop Instead of Act?

arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is

Agile Reinforcement Learning through Separable Neural Architecture and Applications

arXiv:2601.23225v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (RL) is increasingly deployed in resource-constrained environments, yet go-to function approximators - multilayer

Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark

arXiv:2606.30170v1 Announce Type: cross Abstract: Generative molecular design is shaped by simple proxy benchmarks for drug-like properties and models pretrained on large pharmaceutical datasets. This

Boundary Degree as a Node-level Feature for Epidemic Scenario Identification in Agent-based Cascade Simulations

arXiv:2606.29596v1 Announce Type: cross Abstract: Characterizing the scenario underlying an epidemic from its disease cascade is an important task in simulation analytics. We propose boundary degree,

agentsarxiv-cs-lg

CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation

arXiv:2603.06866v3 Announce Type: replace Abstract: Developing autonomous mobile robot systems typically requires either extensive, platform-specific data collection or relies on simplified abstractio

agentsarxiv-cs-ro

CAREBench: A Child-Safety Risk Benchmark for Language Models

model-releasesarxiv-cs-lg

arXiv:2606.29685v1 Announce Type: new Abstract: How can we evaluate whether frontier AI systems recognize child-safety risks before they escalate into explicit harm? Existing child safety evaluations

Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem

arXiv:2606.29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combin

safetyarxiv-cs-ai

CMSL: Constructive Multi-Sequence Learning for Recommendation Systems

arXiv:2606.28533v1 Announce Type: cross Abstract: Sequence learning has emerged as the promising paradigm in recommendation systems, surpassing traditional Deep Learning Recommendation Models (DLRM) b

researcharxiv-cs-ai

Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction

arXiv:2606.30035v1 Announce Type: new Abstract: Free-viewing gaze data provides a rich, task-free window into human visual attention. Conventional exploratory data analysis of the data provides user a

researcharxiv-cs-cv

Data and Evaluation Closed-Loop for Model Capability Enhancement

arXiv:2606.28471v1 Announce Type: new Abstract: Model capability is the central variable in LLM pre-training, yet is never observed directly: data shapes it prospectively, while evaluation reveals it

Local Ai

Data-Driven Modeling and Control for Tethered Space Systems with Koopman-Informed Graphs

arXiv:2606.29825v1 Announce Type: new Abstract: Modeling tethered space systems is critical for advanced orbital operations. Flexible components such as tethers and space nets are integral to these sy

local-aiarxiv-cs-ro

Demonstration-Free Robotic Control via LLM Agents

arXiv:2601.20334v2 Announce Type: replace-cross Abstract: Robotic manipulation has increasingly adopted vision-language-action (VLA) models, which achieve strong performance but typically require task

Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

arXiv:2606.28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditi

DistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articles

model-releasesarxiv-cs-cl

arXiv:2606.29130v1 Announce Type: new Abstract: We present DistilledGemma, an efficient and accurate system for the HIPE-2026 shared task on person-place relation extraction from multilingual historic

Evolutional Math: Cross-Validated Island-Model Genetic Programming for Interpretable Symbolic Regression on Small, Wide Datasets

arXiv:2606.28381v1 Announce Type: cross Abstract: Symbolic regression via genetic programming routinely fails on small, wide datasets - a regime common in clinical-trial monitoring, biostatistics, and

Expert Evaluation of Clinical AI Tools on Real Point-of-Care Clinical Queries

arXiv:2606.28960v1 Announce Type: new Abstract: Physicians now pose millions of clinical questions to AI tools each week, yet these tools are evaluated largely on hypothetical or exam-style questions,

Explaining Attention with Program Synthesis

arXiv:2606.19317v2 Announce Type: replace-cross Abstract: A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descrip

Hardware

GPU-Accelerated Inverse Structural Anastylosis from Block Collapse Dynamics

arXiv:2606.28394v1 Announce Type: new Abstract: The physical anastylosis of collapsed architectural monuments -- the meticulous reassembly of fallen stone elements into their original structural confi

hardwarearxiv-cs-cv

How Much Due Diligence Before You Bid? Learning in Intractable Takeover Auctions

arXiv:2606.29457v1 Announce Type: new Abstract: When two companies bid to buy the same target, no one knows exactly what the target is worth. Each bidder pays for due diligence: costly, imperfect home

researcharxiv-cs-ai

How Should World Models Be Evaluated for Embodied Decision-Making? A Decision-Making-Centric Position

arXiv:2606.15032v2 Announce Type: replace Abstract: World models have become a central abstraction in modern AI. The term now refers to several different objects: action-conditioned environment models

safetyarxiv-cs-lg

Local Ai

How to Leverage Synthetic Speech for LLM-Based ASR Systems?

arXiv:2606.29031v1 Announce Type: cross Abstract: In regulated domains such as banking and healthcare, where privacy constraints make real speech costly to collect and retain, synthetic speech from mo

local-aiarxiv-cs-ai

HyphaeDB: A Living Knowledge Topology for Agent-First Memory

arXiv:2606.28781v1 Announce Type: new Abstract: Every existing vector database and agent memory framework treats memory as passive storage that agents query explicitly. No system propagates knowledge

agentsarxiv-cs-ai

Implementation of Hyperelastic Physics-Augmented Neural Networks in the Explicit Finite Element Codes Simcenter Radioss and OpenRadioss with Applications to Impact Events

arXiv:2606.29874v1 Announce Type: cross Abstract: Data-driven material modeling techniques have gained significant attention due to their ability to capture complex constitutive behaviors beyond the l

researcharxiv-cs-lg

Inference-time optimization for experiment-grounded protein ensemble generation

arXiv:2602.24007v3 Announce Type: replace-cross Abstract: Protein function relies on dynamic conformational ensembles, yet current generative models like AlphaFold3 often fail to produce ensembles tha

safetyarxiv-cs-lg

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing

arXiv:2507.07056v2 Announce Type: replace-cross Abstract: The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightwe

safetyarxiv-cs-lg

MaDI-Bench: An End-to-End Data Integration Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.30371v1 Announce Type: cross Abstract: Data integration combines heterogeneous data sets into a single, coherent representation. Data integration involves a sequence of interdependent tasks

Mechanistic Personality Analysis of LLMs Steering Personality via Latent Feature Interventions

arXiv:2606.28770v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated the ability to simulate human-like OCEAN personality traits in generated text. Previous efforts have focu

researcharxiv-cs-ai

Metric Aggregation Divergence: A Hidden Validity Threat in Agent-Based Policy Optimization and a Contractual Remedy

arXiv:2606.29038v1 Announce Type: cross Abstract: Metric aggregation divergence (MAD) is the silent inconsistency that arises when distinct pipeline stages in an agent-based model coupled with a multi

safetyarxiv-cs-ai

MIThinker: A Plug-and-Play Policy-Optimized Thinker For Motivational Interviewing Counseling

arXiv:2606.29265v1 Announce Type: new Abstract: Reasoning large language models (LLMs) have recently made much progress in complex problem-solving, leveraging internal reasoning (or thought) to guide

safetyarxiv-cs-cl

Modeling Earth-Scale Human-Like Societies with One Billion Agents

arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat

agentsarxiv-cs-ai

Parametric Skills

model-releasesarxiv-cs-cl

arXiv:2606.30015v1 Announce Type: new Abstract: Since intelligence fundamentally relies on efficient skill acquisition (Chollet, 2019), the ability to leverage skills is critical. For LLMs, skills, ma

PCGD: Physics-Guided Conditional Graph Diffusion for TCAD Device Simulation

model-releasesarxiv-cs-lg

arXiv:2606.29272v1 Announce Type: new Abstract: Technology computer-aided design (TCAD) semiconductor device simulation is fundamentally constrained by the high computational cost of iteratively solvi

PlantExpertVQA: A Visual Question Answering Dataset for Benchmarking Vision-Language Models in Plant Science

arXiv:2508.17117v3 Announce Type: replace-cross Abstract: Existing plant-disease datasets target classification and detection, leaving vision-language models unable to support interactive, reasoning-b

Pointer-CAD v2: Plan-Then-Construct CAD Generation with Dimension-Aware Parametric Precision

model-releasesarxiv-cs-cv

arXiv:2606.29301v1 Announce Type: new Abstract: Computer-aided design (CAD) plays a fundamental role in modern manufacturing by providing the high precision required for industrial production. Recent

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation

arXiv:2606.28998v1 Announce Type: cross Abstract: Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM

SAGA: Scene-Aware, Goal-Evolving Agents for Long-Horizon CivRealm Strategy Planning

arXiv:2606.29932v1 Announce Type: new Abstract: Long-horizon strategic planning in complex strategy games demands concurrent reasoning across multiple decision domains under imperfect information and

agentsarxiv-cs-ai

Scaling Textual Gradients via Sampling-Based Momentum

arXiv:2506.00400v4 Announce Type: replace-cross Abstract: LLM-based prompt optimization, which uses LLM-provided ``textual gradients'' (feedback) to refine prompts, has emerged as an effective method

Local Ai

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models

arXiv:2506.20771v2 Announce Type: replace Abstract: We propose a latent score-based generative AI framework for learning stochastic, non-local closure models and constitutive laws in nonlinear dynamic

local-aiarxiv-cs-lg

Hardware

Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries

arXiv:2602.04940v2 Announce Type: replace Abstract: Deep learning has emerged as a transformative tool for the neural surrogate modeling of partial differential equations (PDEs), known as neural PDE s

hardwarearxiv-cs-lg

TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents

arXiv:2606.28480v1 Announce Type: cross Abstract: As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader ra

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform

arXiv:2606.30456v1 Announce Type: cross Abstract: This project investigates whether recent Vision-Language-Action (VLA) models can be transferred from controlled research benchmarks to a real-world ro

safetyarxiv-cs-cv

Weak Dominant Balance for Robust Identification of Dynamically Consistent Fluid Flow Structure

arXiv:2606.29047v1 Announce Type: cross Abstract: Extracting interpretable, localized physical mechanisms from complex spatiotemporal data is a foundational challenge across physics, biology, and engi

researcharxiv-cs-lg

Applications

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate

arXiv:2512.03578v3 Announce Type: replace-cross Abstract: Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series. It appears in

applicationsarxiv-cs-ai

XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation

arXiv:2412.15529v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLM