Search: “engineering”

Operationally Feasible Synthetic Power-Grid Scenarios via Learning the AC-Operable Joint Distribution

arXiv:2608.03878v1 Announce Type: new Abstract: Synthetic power-grid scenarios are essential for planning, resilience assessment, contingency analysis, and data-driven power-system applications. Recen

5 Aug 2026

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Research

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models

DGX agent

arXiv:2608.03057v1 Announce Type: new Abstract: Static quantization assigns one weight precision to every denoising step. To preserve quality, that precision must accommodate the most quantization-sen

researcharxiv-cs-cv

5 Aug 2026

HarnessCompass: Guiding Automatic Harness Evolution toward Generalizable and Effective Agent Harnesses

model-releasesarxiv-cs-cl

arXiv:2608.01918v1 Announce Type: cross Abstract: Harness design plays a critical role in agent performance by shaping how large language models (LLMs) perceive, reason over, and act within executable

4 Aug 2026

Local Ai

PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding

arXiv:2601.02457v2 Announce Type: replace Abstract: Current foundation models for 3D shapes excel at global tasks (retrieval, classification) but transfer poorly to local part-level reasoning. Recent

local-aiarxiv-cs-cv

4 Aug 2026

Agentic Harness for Real-World Compilers

arXiv:2603.20075v2 Announce Type: replace-cross Abstract: Compilers are critical to modern computing, yet fixing compiler bugs is difficult. While recent large language model (LLM) advancements enable

ALIVE: Warnings Before Exclusion in Budgeted Multi-Source Learning

arXiv:2607.29400v1 Announce Type: new Abstract: A routing decision can be revised at the next transaction, but a latched source exclusion persists across later decisions. We ask what evidence should a

researcharxiv-cs-lg

Local Ai

Best Friends, Not Forever: Evaluating Long-Horizon Persona Collapse and Behavioral Drift in AI Companions

arXiv:2607.28818v1 Announce Type: new Abstract: As AI companions increasingly mediate repeated social interaction, users may rely on a stable role and shared history, yet locally acceptable replies do

local-aiarxiv-cs-ai

Bootstrapping Self-Supervised Learning of Binary Classification Using Error Bounds: A Case Study on a Robotic Insertion Task

model-releasesarxiv-cs-ro

arXiv:2607.29640v1 Announce Type: new Abstract: Flexible manufacturing requires rapid deployment of solutions and minimal setup time to remain competitive. An essential attribute is the ability to con

BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning

model-releasesarxiv-cs-cv

arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and fai

Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery

arXiv:2603.03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery. However, rig

InferQ: A Database-Oriented Benchmark for Quantum Circuits Simulation

arXiv:2607.29134v1 Announce Type: cross Abstract: Recent work suggests that relational database management systems (RDBMSs) can execute quantum circuit simulation by compiling the simulation into SQL

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

Unanticipated Effects of Generative AI on Expertise Pathways and Performance Perception in System Administration

arXiv:2607.28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI i

A Graph-Native Bitemporal Memory Store for Conversational AI Agents

arXiv:2607.26520v1 Announce Type: cross Abstract: Conversational AI agents commonly lack persistent memory across sessions. The obvious fixes like injecting full chat histories into the context window

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize

arXiv:2607.27389v1 Announce Type: new Abstract: Learning-to-optimize (L2O) methods accelerate repeated optimization by training models to predict solutions, warm starts, branching decisions, or other

researcharxiv-cs-lg

IFCMemoryBench: Evaluating Long-Term Memory of LLM-Based Agents in BIM Information Retrieval

arXiv:2607.26072v1 Announce Type: cross Abstract: Long-term memory is becoming a core capability of LLM-based agents, but existing evaluations largely test conversational recall in open-domain or pers

KernelGenBench: A Multi-Source and Multi-Chip Benchmark for LLM-based Kernel Generation

arXiv:2607.27231v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly increased the demand for efficient accelerator kernels, but kernel development remains a highly specia

Learning Social Robot Navigation By Sensing Human Legs

arXiv:2607.27922v1 Announce Type: new Abstract: Robots navigating among pedestrians typically sense their surroundings with a 2D LiDAR mounted close to the ground. At that height, the sensor mostly se

safetyarxiv-cs-ro

LM-GRASP: Instance-Specific Language Models for Combinatorial Construction via Online Imitation Learning

arXiv:2607.28135v1 Announce Type: new Abstract: Machine learning for combinatorial optimization typically relies on neural constructors trained via reinforcement learning on large offline datasets for

Partner Capability Estimation for Task-Agnostic Adaptation in Ad-Hoc Teamwork

arXiv:2607.27177v1 Announce Type: new Abstract: Effective collaboration with novel and diverse partners is a crucial skill for autonomous agents. Most current ad-hoc teamwork (AHT) approaches assume t

PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories

arXiv:2607.26464v1 Announce Type: cross Abstract: Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-center

RoboBRIDGE: A Modular Framework for Bridging Policies to Robust Real-World Robotic Agents

arXiv:2607.27881v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have attracted growing interest as a scalable approach to robotic manipulation. While these models are effective act

agentsarxiv-cs-ro

Safety-Gated Agentic Supervisory Control on a Coupled Distillation Benchmark: Regime Map, Auditable Gate, and Co-Design Findings

arXiv:2607.27849v1 Announce Type: cross Abstract: An open-weight LLM can write composition setpoints every five minutes. What a plant still needs is a hard check: named constraints, logged margins, an

Can AI agents conduct open-ended AI research? Early evidence from two case studies

arXiv:2607.27191v1 Announce Type: cross Abstract: Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is t

agentsarxiv-cs-lg

30 Jul 2026

InferScale: GPU-Native KV Injection for Personalized LLM Serving

arXiv:2607.27090v1 Announce Type: cross Abstract: Large language models are increasingly deployed with persistent personalized context, such as accumulated memory profiles or long conversation histori

30 Jul 2026

A Coulomb Particle Model for Learning Kernel Attention in Transformers

arXiv:2607.23869v1 Announce Type: cross Abstract: Randomized features provide a scalable approximation to kernel machines, but their performance depends strongly on the choice of feature distribution.

ACRL: Adaptive Control of Training-Inference Discrepancy for Stable Reinforcement Learning

arXiv:2607.24062v1 Announce Type: cross Abstract: Reinforcement Learning (RL) training for Large Language Models (LLMs) often suffers from instability due to the discrepancy between training and infer

Confidently Wrong: Exception Chain Collapse in Frontier LLM Rule Evaluation

arXiv:2607.23386v1 Announce Type: new Abstract: We document a failure class in frontier large language models -- exception chain collapse -- observed in eligibility evaluation under nested conditional

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds

arXiv:2607.23448v1 Announce Type: cross Abstract: Expensive constrained optimization problems in real-world industry design often involve constraint thresholds that are difficult to determine in advan

CRAFT: Learn the Schema, Execute the Plan

arXiv:2607.22642v1 Announce Type: new Abstract: Enterprise coding agents translate natural-language analytical requests into executable code over proprietary APIs, schemas, and metric definitions. Yet

EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations

model-releasesarxiv-cs-cv

arXiv:2607.22705v1 Announce Type: new Abstract: Object-centric learning aims to represent scenes as objects whose properties can be reused in new combinations. Existing evaluations usually score segme

Frequency-Aware Dual-Stream Learning for Balanced Realism and Fidelity in Electron Microscopy Imaging

arXiv:2607.22765v1 Announce Type: cross Abstract: Electron microscopy enables nanoscale cellular visualization but faces a trade-off between imaging resolution and acquisition speed. Existing learning

researcharxiv-cs-cv

Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning

arXiv:2607.23605v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across

Tutorials

Integrating Factual and Normative Industrial Knowledge via Constraint-Aware Graph Attention for Process Plan Recommendation

arXiv:2607.24213v1 Announce Type: new Abstract: Integrating heterogeneous industrial knowledge, including factual relations and decision constraints, remains a core challenge in industrial information

tutorialsarxiv-cs-ai

Lexical discovery in unknown environments orchestrated by Large Language Models

arXiv:2607.22591v1 Announce Type: new Abstract: Populations of autonomous agents deployed in unknown environments (e.g. planetary or deep-sea exploration) must develop shared vocabularies to refer to

PD^3: A Project Duplication Detection Framework via Adapted Multi-Agent Debate

arXiv:2505.17492v2 Announce Type: replace Abstract: Project duplication detection is critical for project quality assessment because it helps avoid investment in repeated proposals. Existing methods u

Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment

arXiv:2508.02929v3 Announce Type: replace-cross Abstract: Scaling laws have been established for recommender systems, yet efficiently deploying foundation model (FM) across multiple recommendation sur

researcharxiv-cs-ai

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

arXiv:2607.23933v1 Announce Type: cross Abstract: As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces

Test-Time Coverage: Test-Conditioned Data Curation for Deployment-Aware Learning

arXiv:2607.22697v1 Announce Type: new Abstract: Deployed AI systems are often trained from broad candidate data pools, necessitating data curation towards the deployment test distribution. However, st

Applications

TRACE: Business Rule-Grounded Reasoning Curriculum for Knowledge-Preserving Parametric Tool Retrieval in Enterprise LLMs

arXiv:2607.22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via co

applicationsarxiv-cs-ai

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

arXiv:2607.21694v1 Announce Type: new Abstract: We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is

researcharxiv-cs-cv

27 Jul 2026

Chess_db: A framework for working with large chess game datasets

arXiv:2607.21195v1 Announce Type: cross Abstract: Chess is a two player strategic game that is embedded in classical AI culture as it was once the frontier for intelligent behaviour. There was the sil

researcharxiv-cs-ai

Euclid-MCP: A Model Context Protocol Server for Deterministic Logical Reasoning via Prolog

arXiv:2607.21412v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at natural language understanding and generation but remain unreliable for multi-step logical reasoning, especially i

GS-Agent: Creating 4D Physical Worlds With Generative Simulation

arXiv:2607.21522v1 Announce Type: cross Abstract: Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graph

InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents

arXiv:2607.20468v1 Announce Type: new Abstract: AI agents are increasingly used to automate research and development tasks, yet existing benchmarks typically evaluate them on prescribed workflows or n

Is MoE Routing a Huffman Code? Discovering the Frequency-Diversity Law in Chain-of-Thought

arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover

PILD: Physics-Informed Learning via Diffusion

arXiv:2601.21284v2 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents

arXiv:2602.10226v2 Announce Type: replace-cross Abstract: Optimizing large-scale machine learning systems, such as recommendation models for global video platforms, requires navigating a massive hyper