Search: “engineering”

MutMem-V2: Cryptographically Authorized Mutation in Persistent Agent Memory Portable Verification and Reproducible Evidence

arXiv:2609.01235v1 Announce Type: cross Abstract: MutMem V1 introduced retention-preserving, cryptographically authorized mutation for persistent agent memory but did not provide a complete portable v

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NewsRECON: News Article Retrieval for Image Contextualization

DGX agent

arXiv:2601.14121v2 Announce Type: replace Abstract: Identifying when and where a news image was taken is crucial for journalists and forensic experts to produce credible stories and debunk misinformat

model-releasesarxiv-cs-cl

2 Sept 2026

Nonlinear Dynamics In Optimization Landscape of Shallow Neural Networks with Tunable Leaky ReLU

model-releasesarxiv-cs-lg

arXiv:2510.25060v2 Announce Type: replace-cross Abstract: In this work, we study the nonlinear dynamics of a shallow neural network trained with mean-squared loss and leaky ReLU activation. Under Gaus

On Global Regulatability of Robot Manipulators by Classical PID

model-releasesarxiv-cs-ro

arXiv:2609.01207v1 Announce Type: new Abstract: This paper studies a class of uncertain multi-input multi-output (MIMO) nonlinear systems using extended PID (EPID) control. We focus on systems possess

Industry

OpenMatter adds an AI model gateway and privacy-preserving machine learning

OpenMatter Network Inc. today announced the first significant expansion of its platform since its commercial launch three months ago, adding a developer kit, a gateway for managing access to artificia

industrysiliconangle

PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition

arXiv:2609.01024v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures scale Large Language Model (LLM) capacity efficiently by activating a sparse subset of experts per token. However

Quad R9700 AI Pro with vLLM-Radiance easily reaching 17,6k PP

model-releasesr-localllama

https://preview.redd.it/74bmvel9b5nh1.png?width=1602&format=png&auto=webp&s=0d0c1adaa016a486ffd97c4c466e980dc611b139 I've only recently started looking deeper into vLLM after running llama.cpp for a g

S^3martCirc: Self-supervised Smart Circuit Discovery

arXiv:2609.00755v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks, from text summarization to question answering. Despite these

Solaris: Towards Interfaces That Are Generated, Not Coded

arXiv:2609.00776v1 Announce Type: cross Abstract: Digital interfaces are traditionally implemented through intermediate representations such as code, requiring their appearance and behavior to be spec

SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generation

arXiv:2609.00427v1 Announce Type: new Abstract: The exponential growth of wireless devices is driving unprecedented spectrum demand, pushing spectrum management toward more fine-grained decisions acro

safetyarxiv-cs-ai

Tutorials

SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding

arXiv:2609.01353v1 Announce Type: new Abstract: Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineerin

tutorialsarxiv-cs-ai

This 'recurrent depth' is essentially what's in Sec. 5.3 of the 2015 paper: On Learning to Think: Algorithmic Information Theory for Novel C…

This 'recurrent depth' is essentially what's in Sec. 5.3 of the 2015 paper: On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurr

researchdavid-ha--x

Vision Is Not Overhead: One-Pass Block Drafting for Lossless Speculative Decoding in Vision-Language Models

arXiv:2609.00355v1 Announce Type: new Abstract: Speculative decoding accelerates generation without changing its output, yet on vision-language models (VLMs) it has been caught in a self-defeating cyc

applicationsarxiv-cs-ai

A Comprehensive Survey on Linguistic Steganography: Methods, Countermeasures, Evaluation, and Challenges

arXiv:2608.29077v1 Announce Type: cross Abstract: Linguistic steganography hides secret messages in natural language text. Large language models (LLMs) have reshaped the field, but a systematic accoun

A Human-in-the-Loop Autonomous Agent for Industry Time Series Forecasting

arXiv:2608.30976v1 Announce Type: new Abstract: Real-world time-series forecasting is rarely a one-shot model invocation: practitioners must formulate tasks, connect data and models, incorporate domai

agentsarxiv-cs-lg

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl

An Agentic Retrobiosynthesis Framework with Learned Frontier Selection

arXiv:2608.30702v1 Announce Type: cross Abstract: Large language models are increasingly used as agents for multistep retrosynthesis, raising the question of how much their search policy contributes i

An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process

arXiv:2603.13584v3 Announce Type: replace-cross Abstract: Deep learning has achieved recognition for its impact within natural sciences, yet the prohibitive financial and technical cost of training mo

An Open-Source, Event-Driven Pipeline for Cryptocurrency Market Data: Ingestion, Forecasting, and On-Chain Fraud Detection

arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an

APIFlow-Bench: Measuring Whether Agents Survive Long, Dependent API Workflows

arXiv:2608.29128v1 Announce Type: new Abstract: Tool-using agents are commonly evaluated by a single bit: whether an end-to-end workflow completed. This metric fails to distinguish failures that matte

Aspire: Can Models Self-Evolve from Vague Goals?

model-releasesarxiv-cs-cl

arXiv:2608.31111v1 Announce Type: new Abstract: Many important forms of human learning begin with a vague goal, such as 'become a better physicist' or 'improve at research.' Learners must interpret th

Attribute-Based Activation Steering of LLMs for Group-Specific Explanation Generation

arXiv:2608.29215v1 Announce Type: new Abstract: To effectively enable people to understand new topics, explanations should be tailored to their backgrounds and abilities. So far, prompting alone has b

A.X K2 Technical Report

arXiv:2608.30181v1 Announce Type: new Abstract: We introduce A.X K2, a 688B-parameter Mixture-of-Experts (MoE) language model trained from scratch as a high-performance foundation for agentic applicat

Beyond Churn: Predicting Financial Fragmentation in Retail Banking with Temporal Machine Learning

arXiv:2608.30364v1 Announce Type: new Abstract: Retail banking attrition is usually represented as a terminal binary event, even though client relationships often weaken earlier through partial moveme

researcharxiv-cs-lg

Beyond Surface Alignment: Grounding the Dynamics of Situational Understanding and Generative Control in LLMs

arXiv:2608.29610v1 Announce Type: new Abstract: The current alignment tuning paradigm for Large Language Models (LLMs) prioritizes surface-level behaviors -- fluency, safety, and tonal consistency. Wh

safetyarxiv-cs-cl

DASC: Decay-Aware State Compression for Hybrid Linear-Attention Serving

arXiv:2608.30386v1 Announce Type: cross Abstract: Hybrid linear-attention architectures have recently scaled to large open-weight models, offering quality competitive with full attention while substan

Data-Driven Design Optimization of Streaming-Potential-Mediated Electrokinetic Transport of Viscoelastic Fluids in Microchannels

model-releasesarxiv-cs-lg

arXiv:2608.29939v1 Announce Type: cross Abstract: Streaming-potential-mediated transport of viscoelastic fluids has attracted research attention owing to its applications in electrokinetic energy conv

Delegating Before Learning: Where Generative AI Sits in Students' Professional Communication

arXiv:2608.28837v1 Announce Type: cross Abstract: We conducted an interview study with twelve students on their use of generative AI in academic communication. Students delegated professional messages

safetyarxiv-cs-ai

Deploying DeepSeek 175B Locally on a Single Consumer-Grade RTX 4060 Laptop with 32GB RAM for 200k-Scale Protein-Ligand Virtual Screening

model-releasesarxiv-cs-lg

arXiv:2608.30877v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated exceptional performance in protein-ligand interaction prediction, but state-of-the-art

Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environments

arXiv:2608.29907v1 Announce Type: new Abstract: Future wireless systems are expected to transform the surrounding space from a passive propagation medium into a smart electromagnetic environment, wher

researcharxiv-cs-lg

Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice

arXiv:2507.05512v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for code generation, making reliable identification of machine-generated code important for

EviAnchor: Mitigating Hallucinations in Large Vision-Language Models via Regional Visual Evidence Compensation

arXiv:2608.29092v1 Announce Type: new Abstract: Large vision-language models (LVLMs) frequently generate content unsupported by visual inputs. Preliminary experiments show that visual evidence is prim

Explainable Machine Learning for Broadband Adoption Disparities: Tract-Level Prediction and SHAP-Based Factor Profiling

arXiv:2608.29110v1 Announce Type: new Abstract: The United States has allocated approximately $65 billion through the Infrastructure Investment and Jobs Act for broadband expansion, yet evidence-based

applicationsarxiv-cs-lg

Failure or Drift? Evaluating Monocular SLAM under Synthetic and Real-World Corruptions

arXiv:2608.30690v1 Announce Type: new Abstract: Visual SLAM is commonly evaluated on clean trajectories, although deployment failures are often caused by adverse weather, illumination, blur, and senso

applicationsarxiv-cs-cv

From Question-First to Analyst-First: Domain-Expert Skills and Verified Knowledge Compilation for Proactive Enterprise Analytics

arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente

Hallucination Mitigation for Large Vision-Language Models via Implicit Feature Stabilization

arXiv:2608.29924v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) are prone to hallucinations: they fluently describe objects, attributes, and scenes that are not in the image. We

Higher-Dimensional Rotary Position Embedding

arXiv:2608.29715v1 Announce Type: cross Abstract: Transformers rely on position embedding mechanisms in long context modeling in most cases. Rotary Position Embedding (RoPE) embeds positional informat

HintEval: An Open-Source Python Toolkit for Hint Generation and Hint Evaluation

arXiv:2502.00857v2 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly provide direct answers to user questions, raising concerns about reduced engagement in critical thinking a

How do World Models and Policies Compose in LLM Agents? A Joint Spectral and Behavioral Account

arXiv:2608.30067v1 Announce Type: cross Abstract: How do LLM agents come to both understand environments they act in and master tasks set within them? Through controlled experiments combining world-mo

HumanStudy-Bench: Towards AI Agent Design for Participant Simulation

arXiv:2602.00685v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as simulated participants in social science experiments, but their behavior is often unstable and

agentsarxiv-cs-ai

Language-Guided Tuning: Configuration Optimization for Automated ML Research

arXiv:2508.15757v2 Announce Type: replace Abstract: Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strat

agentsarxiv-cs-ai

Local Ai

Learning to infer and manipulate through distributed whole-arm interaction in a soft robot

arXiv:2608.30773v1 Announce Type: new Abstract: In animals such as elephants and octopuses, acquiring non-visual information about an object and physically engaging with it are inseparable processes m

local-aiarxiv-cs-ro

Leveraging Generative AI to Design Accessible Interactive Visualizations for Undergraduate Mathematics: A Six-Phase Workflow

arXiv:2608.28601v1 Announce Type: new Abstract: Interactive visualizations support conceptual understanding in undergraduate mathematics, but building them has required programming expertise most inst

applicationsarxiv-cs-ai

MagicSim: A Unified Infrastructure for Executable Embodied Interaction

arXiv:2606.17511v2 Announce Type: replace-cross Abstract: Robot learning and embodied agents now require simulation to serve as a shared execution substrate linking control, skills, and planning, not

Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory

arXiv:2608.29910v1 Announce Type: new Abstract: Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling applic

researcharxiv-cs-cv

mRNA Design and Optimization with Deep Knowledge-Infused Approach

arXiv:2505.23862v2 Announce Type: replace-cross Abstract: The mRNA optimization is essential for mRNA vaccines, therapies, and industrial protein production. Based on current explorations, an ideal op

applicationsarxiv-cs-ai

N_0-Foundation: Towards the Age of Tactile Intelligence

model-releasesarxiv-cs-cv

arXiv:2608.29601v1 Announce Type: cross Abstract: We present N_0-Foundation, a paradigm for tactile-enabled embodied manipulation, which integrates tactile sensing hardware, large-scale multimodal dat

NBS: No Bias Stereo

arXiv:2608.28933v1 Announce Type: new Abstract: Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias.

safetyarxiv-cs-cv