Search: “engineering”

Passing Tests, Missing Semantics: Evidence of Interpretive Lock-In in Plan-Based DataFrame Code Generation

arXiv:2610.15797v1 Announce Type: new Abstract: Planning and revision are intended to bring generated code closer to the task specification. Yet a mistaken interpretation can persist across the plan,

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Safety

PEARL: Process-Experience Aware Reinforcement Learning for Multi-Turn Agents

DGX agent

arXiv:2610.14636v1 Announce Type: new Abstract: Terminal rewards make multi-turn agents trainable without step-level annotations, but group-relative advantages provide little guidance about which inte

safetyarxiv-cs-ai

15 Oct 2026

PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation

arXiv:2610.19615v1 Announce Type: new Abstract: Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and requi

REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-Teaming

arXiv:2610.15513v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming

SchemaWeaver: Accelerating On-Device Mobile Agentic AI via Schema-Guided Parallel LLM Decoding

arXiv:2610.17436v1 Announce Type: new Abstract: Large language models (LLMs) on mobile devices can act as agents that call external software tools to complete complex tasks, but the major challenge of

local-aiarxiv-cs-ai

SWE-Spot: Building Small Repo-Experts with Repository-Centric Learning

model-releasesarxiv-cs-cl

arXiv:2601.21649v2 Announce Type: replace-cross Abstract: The deployment of coding agents in privacy-sensitive and resource-constrained environments drives the demand for capable open-weight Small Lan

Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance

arXiv:2610.19860v1 Announce Type: cross Abstract: In sectors such as energy, aquaculture and chemical processing, the effectiveness of both mechanistic and data-driven models is frequently limited by

VideoHarness-SRSI: Structured Recursive Self-Improvement for Video Understanding Harness

arXiv:2610.19424v1 Announce Type: new Abstract: LLM system capabilities depend not only on model parameters but also on the executable harnesses that organize information acquisition, tool use, reason

agentsarxiv-cs-cv

Why Agentic Workflows Fail: A Taxonomy Derived from Literature and Empirical Data

arXiv:2610.17418v1 Announce Type: cross Abstract: Agentic workflows combine large language models with planning, memory, tools, execution environments, and iterative feedback. Their failures are diffi

local-aiarxiv-cs-ai

A physics-coupled graph neural operator for mid-plane six-component stress tensor field prediction in concrete penetration

arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o

An Open MuJoCo Simulation Framework for a Quadrotor Carrying a Tendon-Driven Soft Continuum Arm

model-releasesarxiv-cs-ro

arXiv:2610.15308v1 Announce Type: new Abstract: Combining aerial robots with soft continuum manipulators promises safe, compliant interaction with the environment, but the coupled dynamics of a free-f

APTree: Extended Behavior Trees for Adaptive and Scalable Automated Robotic Task Planning in Construction

arXiv:2610.18523v1 Announce Type: new Abstract: Task planning for robots in off-site construction prefabrication is primarily manual, leading to planning inefficiencies and reluctance to adopt robotic

local-aiarxiv-cs-ro

CoEvoke: Evoking Multi-Agent Collaboration for Trajectory Collection

arXiv:2610.14021v1 Announce Type: new Abstract: Training multi-agent collaboration requires trajectories of checking, feedback, and repair, yet task-solving rollouts may end in immediate approval or r

Disentangling Task-Relevant Latent Dynamics for Reward Modeling

arXiv:2610.14159v1 Announce Type: cross Abstract: Reward design remains a major bottleneck for reinforcement learning in robotic manipulation. Handcrafted dense rewards can compensate for the limited

safetyarxiv-cs-cv

Dissecting the Carbon-SLO Tension in Geo-Distributed LLM Serving

arXiv:2610.14571v1 Announce Type: cross Abstract: Large Language Model (LLM) inference is driving a growing share of datacenter carbon emissions. Although carbon-aware scheduling can reduce these emis

safetyarxiv-cs-lg

DRanker: A Transformer-Based Multi-Task Ranking Model for the Disney+ Homepage

arXiv:2610.15696v1 Announce Type: new Abstract: We present DRanker (Disney+ Ranker), a transformer-based multitask ranking model serving personalized recommendations on the Disney+ homepage. We descri

Dynamic Interpolation for Training-Time Prediction Reshaping in Low-Light Image Enhancement

model-releasesarxiv-cs-cv

arXiv:2610.18018v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an important image/video processing problem for reliable visual systems under poor illumination, yet it remains ch

EgoMatrix: Physically Faithful Dexterous Robot Demonstrations from Egocentric Human Videos

arXiv:2610.18822v1 Announce Type: new Abstract: Egocentric human videos offer a scalable alternative to robot teleoperation for collecting dexterous manipulation data. However, two challenges limit th

EgoProbe: Benchmarking Long-Range and Exact Memory in Streaming Egocentric Videos

model-releasesarxiv-cs-cv

arXiv:2610.17128v1 Announce Type: new Abstract: Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike off

Hardware

FastEEP: Fast Intra-Instance Elastic Scaling for Expert-Parallel MoE Serving

arXiv:2610.18451v1 Announce Type: cross Abstract: Large-scale expert parallelism (EP) has become the standard deployment configuration for Mixture-of-Experts (MoE) models in production. Meanwhile, the

hardwarearxiv-cs-lg

From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction

arXiv:2610.16569v1 Announce Type: cross Abstract: Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance lab

Hierarchical Multi-Agent Reasoning Systems for Knowledge-Grounded Material Substitution

arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

model-releasesarxiv-cs-lg

arXiv:2603.21862v2 Announce Type: replace Abstract: Scaling laws govern macroscopic resource allocation for LLMs, yet precise architectural configurations for Mixture-of-Experts (MoE) models remain gu

Hardware

Human-like autonomy emerges from self-play and a pinch of human data

arXiv:2606.19370v2 Announce Type: replace Abstract: Self-play reinforcement learning has recently emerged as a way to train driving policies without any human data. It uses cheap, large-scale simulati

hardwarearxiv-cs-lg

Imitation Learning via Discrete and Rhythmic Primitive Composition

arXiv:2610.15639v1 Announce Type: new Abstract: Long-horizon robotic manipulation is inherently composed of semantically meaningful sub-tasks. While Movement Primitives (MPs) can model these component

InfoVis: Unified Slide Image Generation and Editing

model-releasesarxiv-cs-cv

arXiv:2610.16784v1 Announce Type: new Abstract: Generating and editing presentation slides requires models to combine accurate text rendering, instruction following, visual grounding, aesthetic design

Tutorials

Learning from fracture: Teaching language models to design through physical experience

arXiv:2610.17804v1 Announce Type: cross Abstract: How can language models learn to optimize physical designs through experience? We introduce FracLearn, an experience-abstraction-generalization framew

tutorialsarxiv-cs-lg

Learning to Assist: Collaborative VLAs for Implicit Human-Robot Collaboration

arXiv:2606.12475v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) combines the complementary strengths of humans and robots to improve task efficiency. However, many existing collabo

LocalTrain: Integer-Only Local Learning for Energy-Efficient CNN Training on Edge FPGAs

arXiv:2610.17099v1 Announce Type: cross Abstract: Local learning reduces cross-layer training dependencies, but an efficient accelerator must still retain operands, accumulate gradients, and select qu

OneDemo: Unified Policy Learning and Data Generation from a Single Demonstration

arXiv:2610.18188v1 Announce Type: new Abstract: Learning robot policies from demonstrations is often limited by the cost of collecting diverse, high-quality expert data. While an appealing alternative

Prorsa: Unleashing the Potential of Prefill-Decode Disaggregation in Agentic Reinforcement Learning

arXiv:2610.16592v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) is commonly used to enhance the capabilities of large language models (LLMs) in solving complex multi-turn tasks.

Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

arXiv:2512.03923v3 Announce Type: replace Abstract: Solving reservoir seepage partial differential equations (PDEs) is critical for hydrocarbon development optimization and production forecasting. Con

Quasicrystal Architected Nanomechanical Resonators via Data-Driven Design

arXiv:2604.07379v2 Announce Type: replace-cross Abstract: From butterfly wings to remnants of nuclear detonation, aperiodic order repeatedly emerges in nature, often exhibiting reduced sensitivity to

Query-Adaptive Neuron Steering for LLMs

model-releasesarxiv-cs-lg

arXiv:2610.14519v1 Announce Type: new Abstract: Effectively eliciting the capabilities of large language models (LLMs) at inference time remains an important challenge. Existing studies address this c

Requests of a Feather Must Flock Together: Batch Size vs. Prefix Homogeneity in LLM Inference

arXiv:2605.06046v2 Announce Type: replace Abstract: Auto-regressive token generation in large language models is memory-bound because it requires 'attending to' key and value tensors (KV cache) of all

local-aiarxiv-cs-lg

SLDBench v2: Active Scaling Law Discovery

arXiv:2610.16297v1 Announce Type: new Abstract: Scaling laws predict large-model performance from small experiments, but finding a reliable law itself requires costly experiments. SLDBench tests wheth

Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data

arXiv:2610.14105v1 Announce Type: cross Abstract: Accurate artery extraction from X-ray coronary angiography (XCA) is essential for coronary artery disease diagnosis and intervention. However, low ves

researcharxiv-cs-cv

The Value of Being Wrong: Self-Mined Visual In-Context Learning from Errors

arXiv:2610.16977v1 Announce Type: new Abstract: Visual in-context learning (ICL) enables vision-language models (VLMs) to adapt at test time via demonstration examples, but its effectiveness depends c

researcharxiv-cs-cv

AgentSWE: Can Coding Agents Build the Agent You Actually Want?

arXiv:2610.13361v1 Announce Type: cross Abstract: As the production of software passes into the hands of software itself, coding agents are increasingly commissioned to build agents fitted to their us

Algebraic Integer Quantization for Machine Learning Applications

model-releasesarxiv-cs-lg

arXiv:2610.12494v1 Announce Type: new Abstract: In this article, we propose algebraic integer number formats (AINF) as a framework for highly configurable and accurate compressed computation. A key pr

CoBe: A Benchmark For Conversational Counterfactual Text Editing

arXiv:2610.13057v1 Announce Type: cross Abstract: Counterfactual text editing is the ability to revise a given text in light of a hypothetical change while preserving facts not causally affected by th

DRYLAB-Bench: Benchmarking the Biosecurity Risk of Agentic LLM Mutation Design

arXiv:2610.13116v1 Announce Type: new Abstract: As large language models (LLMs) acquire advanced biological design capabilities, they offer substantial research benefits but simultaneously introduce s

Energy-Efficient Spiking Neural Networks for Sensing-Aided Beam Prediction

arXiv:2610.12507v1 Announce Type: cross Abstract: Sensing-aided beam prediction can reduce the beam-training overhead of millimeter-wave (mmWave) systems by leveraging environmental information from c

researcharxiv-cs-ai

Grounded-Dreamer: Robot Learning from World Model Synthetic Data with Physical Grounding

arXiv:2610.13164v1 Announce Type: new Abstract: Scaling robot manipulation policies requires large amounts of diverse, action-labeled data, yet collecting such data in the real world remains expensive

HumanX: Toward Agile and Generalizable Humanoid Interaction Skills from Human Videos

arXiv:2602.02473v2 Announce Type: replace-cross Abstract: Enabling humanoid robots to perform agile and adaptive interactions has long been a core challenge in robotics. Current approaches are bottlen

KITE: A Knowledge-Injected Temporal Encoder for Time-Series Event Forecasting

arXiv:2610.12738v1 Announce Type: cross Abstract: Forecasting rare, high-cost events in multivariate time-series systems is hard because their precursors are seldom observed, so a purely data-driven m

safetyarxiv-cs-ai

Meta-Reflective Evolution Effectively Improves Production AI Systems

arXiv:2610.12794v1 Announce Type: cross Abstract: Large Language Model (LLM)-guided evolutionary optimization has successfully improved prompts, programs, and even entire AI systems. Most optimization

agentsarxiv-cs-ai

Oido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

model-releasesarxiv-cs-cl

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oido, an inferenc