Search: “engineering”

The 4/elta Bound: Designing Predictable LLM-Verifier Systems for Formal Method Guarantee

arXiv:2512.02080v3 Announce Type: replace-cross Abstract: The integration of Formal Verification tools with Large Language Models (LLMs) offers a path to scale software verification beyond manual work

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

The Interplay of Harness Design and Post-Training in LLM Agents

DGX agent

arXiv:2606.25447v1 Announce Type: cross Abstract: Tool-integrated LLM agents are often wrapped within a harness: the scaffolding that determines which tools are exposed, how they are described, and wh

researcharxiv-cs-cl

25 Jun 2026

Toten: A Knowledge-Based System For Structure-Preserving Representation Of Physical Quantities And Technical Notation In Brazilian Portuguese

model-releasesarxiv-cs-cl

arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expression

Agents

VADAOrchestra: Neurosymbolic Orchestration of Adaptive Reasoning Workflows

arXiv:2606.22485v2 Announce Type: replace-cross Abstract: Decision-making in real-world settings rarely follows a fixed script. Instead, it unfolds as a dynamic reasoning process in which the appropri

agentsarxiv-cs-cl

Weave of Formal Thought

arXiv:2606.25987v1 Announce Type: new Abstract: Large language models (LLMs) attain remarkable surface fluency on code, yet they neither formally guarantee the syntactic validity of their output nor l

researcharxiv-cs-cl

A Benchmark of State-Space Models vs. Transformers and BiLSTM-based Models for Historical Newspaper OCR

model-releasesarxiv-cs-cv

arXiv:2604.00725v2 Announce Type: replace Abstract: End-to-end OCR for historical newspapers remains challenging, as models must handle long text sequences, degraded print quality, and complex layouts

A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion

arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools fro

AutoSpecNER: A Fine-Grained Named Entity Recognition Dataset for Vehicle Specification Extraction

model-releasesarxiv-cs-cl

arXiv:2606.24387v1 Announce Type: new Abstract: Vehicle advertisements contain rich specification information, but automotive NER resources remain limited. We introduce AutoSpecNER, an expert-annotate

BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents

model-releasesarxiv-cs-ai

arXiv:2605.06177v2 Announce Type: replace Abstract: Reproducing and comparing deep research agents today is hard: the same backbone evaluated on the same benchmark can report different accuracies acro

Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index

model-releasesarxiv-cs-ai

arXiv:2606.24421v1 Announce Type: new Abstract: Spectral filtering recently delivered substantial pruning for static subgraph matching: Laplacian interlacing rejects candidates whose neighborhoods can

Critique of Agent Model

arXiv:2606.23991v1 Announce Type: new Abstract: What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and

safetyarxiv-cs-ai

Local Ai

CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation

arXiv:2606.24506v1 Announce Type: cross Abstract: Emerging LLM services increasingly host many sparse MoE models, yet most models receive sparse requests and remain cold. This creates a GPU memory pro

local-aiarxiv-cs-ai

Hardware

Differentiable Packing of Irregular 3D Objects with Adaptive Container Estimation

arXiv:2606.16333v2 Announce Type: replace Abstract: Most existing approaches either fix the container in advance or optimize only a single container dimension through an outer search loop, leaving the

hardwarearxiv-cs-cv

Enabling Robust Cloth Manipulation via Inference-Time Simulator-in-the-Loop Refinement

arXiv:2606.24552v1 Announce Type: new Abstract: Simulator-in-the-loop optimization offers a promising inference-time mechanism for robot manipulation. It uses a physical simulator as a backend rollout

safetyarxiv-cs-ro

Local Ai

EnerInfer: Energy-Aware On-Device LLM Inference

arXiv:2606.23001v1 Announce Type: cross Abstract: On-device LLM inference is increasingly attractive for privacy-preserving, reliable, and cost-effective deployment, yet its energy and thermal costs r

local-aiarxiv-cs-lg

FLAT: Feedforward Latent Triangle Splatting for Geometrically Accurate Scene Generation

arXiv:2606.24876v1 Announce Type: new Abstract: Generating explorable 3D scenes from a single image requires strong generative priors and accurate geometric representations suitable for downstream use

researcharxiv-cs-cv

Geometry-Instructed Video Editing

arXiv:2606.24225v1 Announce Type: new Abstract: Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content cr

researcharxiv-cs-cv

Knowledge-Graph Grounding Helps LLMs Only for Out-of-Training Knowledge: A Controlled Study on Clinical Question Answering

model-releasesarxiv-cs-cl

arXiv:2606.22419v2 Announce Type: replace Abstract: A recent Nature Medicine study reports that general-purpose frontier LLMs outperform specialized retrieval-augmented clinical tools on medical bench

Maestro Order: A Model-Agnostic Orchestration Harness

arXiv:2606.23983v1 Announce Type: cross Abstract: A single forward pass of a capable model is a fast, fluent, and unreliable problem-solver: it is right often enough to be useful and wrong often enoug

researcharxiv-cs-ai

Matching Tasks to Objectives: Fine-Tuning and Prompt-Tuning Strategies for Encoder-Decoder Pre-trained Language Models

arXiv:2606.24841v1 Announce Type: new Abstract: Prompt-based learning has emerged as a dominant paradigm in natural language processing. This study explores the impact of diverse pre-training objectiv

researcharxiv-cs-ai

Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAs

model-releasesarxiv-cs-ai

arXiv:2606.23938v1 Announce Type: new Abstract: Driving VLA models incorporating Chain-of-Thought (CoT) reasoning are attractive because they leverage pretrained VLM representations and expose interme

Applications

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials

arXiv:2505.21916v3 Announce Type: replace Abstract: Embodied robots have achieved strong performance in many real-world manipulation tasks, yet agile dynamic manipulation remains challenging due to hi

applicationsarxiv-cs-ro

Sesame: Structure-Aware Molecular Generation via Spatial Density-Map Conditioning

arXiv:2606.23856v1 Announce Type: new Abstract: Generative molecular models for drug design are a promising direction with much active research. In the next phase of computational drug design, such mo

UOL@IDEM at BEA 2026 Shared Task 1: Neural Fusion and Feature-Rich Modeling for L1-Aware Vocabulary Difficulty Prediction

arXiv:2606.24501v1 Announce Type: new Abstract: This paper describes UOL@IDEM's closed-track submission to the BEA 2026 shared task on L1-aware vocabulary difficulty prediction. We model the task as r

safetyarxiv-cs-cl

When CQs Go Wrong: Challenges in CQ Verification with OE-Assist

arXiv:2606.24619v1 Announce Type: new Abstract: Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natur

safetyarxiv-cs-ai

Applications

A Physics-Informed, Behavior-Aware Digital Twin for Robust Multimodal Forecasting of Core Body Temperature in Precision Livestock Farming

arXiv:2604.04098v2 Announce Type: replace Abstract: Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study pr

applicationsarxiv-cs-cv

A Verifiable Search Is Not a Learnable Chain-of-Thought

arXiv:2606.21884v1 Announce Type: new Abstract: It is tempting to assume any task solvable by a short program can be taught to a model as its chain-of-thought: write the steps out, fine-tune, and the

Attention mechanism for scalable mesh-based neural surrogates of free-surface fluids

arXiv:2606.23251v1 Announce Type: cross Abstract: High-fidelity simulations of free-surface flows using Lagrangian methods such as the Particle Finite Element Method (PFEM) are computationally demandi

CogFormer: Learn All Your Models Once

arXiv:2603.20520v2 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) with neural networks has accelerated and transformed cognitive modeling workflows. SBI enables modelers to fi

tutorialsarxiv-cs-lg

CRAX: Fast Safe Reinforcement Learning Benchmarking

arXiv:2606.20376v2 Announce Type: replace Abstract: Safety is a core concern for deploying reinforcement learning (RL) agents in real-world domains such as robotics and autonomous driving. While bench

Decodable but Not Faithful: Coupling Natural-Language Rationales to Programmatic Verifiers

arXiv:2606.21678v1 Announce Type: new Abstract: Language models can generate plausible rationales for their predictions, but these explanations may not faithfully represent the model's internal reason

EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors

arXiv:2602.21218v2 Announce Type: replace-cross Abstract: High-quality data is essential for modern machine learning, yet many valuable corpora are sensitive and cannot be freely shared. Synthetic dat

safetyarxiv-cs-lg

FlowCodec: One-Step Flow Prior for Generative Image Compression

model-releasesarxiv-cs-cv

arXiv:2606.21030v1 Announce Type: cross Abstract: Diffusion-based image compression methods, leveraging powerful generative priors, have demonstrated remarkable perceptual quality at ultra-low bitrate

Applications

From Complaint Narratives to Monetary Relief: A Hybrid Machine Learning Framework for CFPB Consumer Complaints

arXiv:2606.22664v1 Announce Type: cross Abstract: Consumer financial complaints provide a valuable source of information for identifying service failures, dispute frictions, and operational deficienci

applicationsarxiv-cs-lg

GARIP: A Running-Average Moving Reference for Last-Iterate Self-Play in Two-Player Zero-Sum Games

arXiv:2606.22688v1 Announce Type: cross Abstract: Self-play with naive gradient ascent cycles in two-player zero-sum games: the last iterate orbits the equilibrium. Modern methods restore last-iterate

safetyarxiv-cs-lg

Good-Enough LLM Obfuscation (GELO)

arXiv:2603.05035v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly served on shared accelerators where an adversary with read access to device memory can observe K

Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models

arXiv:2606.21672v1 Announce Type: cross Abstract: Imitation learning has emerged as a powerful paradigm for learning visuomotor policies, but its generalisation and stability are limited by the scale

safetyarxiv-cs-lg

Improving Text-to-Music Generation with Human Preference Rewards

arXiv:2606.21670v1 Announce Type: cross Abstract: We describe our entry to the efficiency track of the Academic Text-to-Music (ATTM) Grand Challenge at ICME 2026. Beyond the challenge protocol's FAD-C

Jacobian-Adaptive Weighting for Stability: Enhancing Long-term Rollout of Neural Partial Differential Equation Solvers via Spatially-Adaptive Regularization

arXiv:2603.05538v3 Announce Type: replace Abstract: Data-driven surrogate models can significantly accelerate the simulation of continuous dynamical systems, yet the step-wise accumulation of errors d

Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection

arXiv:2606.22261v1 Announce Type: new Abstract: Abnormality detection in complex systems faces two practical barriers: abnormal labels are scarce, and binary labels do not quantify how far an event ha

LLM-Aided A* Search in Non-Geometric Network Graphs

arXiv:2606.23136v1 Announce Type: cross Abstract: Finding the shortest path in non-geometric network graphs, where edge weights encode arbitrary metrics such as latency or monetary cost rather than sp

tutorialsarxiv-cs-lg

Machine Learning Classification of Cryopathy Syndromes: A Comprehensive Comparative Study

arXiv:2606.20874v1 Announce Type: new Abstract: Cryopathy syndromes are difficult to classify because laboratory patterns often overlap across diagnostic categories, while some diagnoses are rare. Thi

Agents

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning

arXiv:2403.06828v4 Announce Type: replace Abstract: Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision

agentsarxiv-cs-ro

NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations

arXiv:2601.17207v2 Announce Type: replace Abstract: We introduce NewPINNs, a physics-informing learning framework that couples neural networks with conventional numerical solvers for solving different

tutorialsarxiv-cs-lg

Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense

arXiv:2602.09012v2 Announce Type: replace Abstract: The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a

Nous: A Predictive World Model for Long-Term Agent Memory

arXiv:2606.22030v1 Announce Type: cross Abstract: We present Nous, a novel agent memory architecture grounded in the principle that knowledge is prediction, not storage. Rather than persisting facts a

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation

arXiv:2602.24121v2 Announce Type: replace Abstract: Current methods in robot learning are fundamentally bottlenecked by one or more of: hand-designed rewards, simulation modeling, or action supervisio

tutorialsarxiv-cs-ro

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

arXiv:2606.20512v2 Announce Type: replace-cross Abstract: LLM-based coding agents need higher-level operational knowledge about a repository (which files house which subsystems, how to run the test su