Search: “concepts”

arXiv:2511.22226v2 Announce Type: replace Abstract: The standard theory of model-free reinforcement learning assumes that the environment dynamics are stationary and that agents are decoupled from the

agentsarxiv-cs-ai

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Safety

First Investigation of Deep Learning for Intraoperative Gauze Segmentation in Minimally Invasive Abdominal Surgery

DGX agent

arXiv:2607.29132v1 Announce Type: new Abstract: Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical reten

safetyarxiv-cs-cv

3 Aug 2026

Information Processing by Neuron Populations in the Central Nervous System: A Theory of the Mathematical Structure of Data and Operations

arXiv:2309.02332v3 Announce Type: replace-cross Abstract: In the mammalian central nervous system, neurons are organized into populations communicating by spike trains propagating along axonal bundles

researcharxiv-cs-ai

Local Ai

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

arXiv:2512.03438v3 Announce Type: replace Abstract: Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally opt

local-aiarxiv-cs-ai

Persistent Convolution: A Topological Framework for AI Alignment Testing and Semantic Space Characterization

arXiv:2607.29008v1 Announce Type: cross Abstract: Modern opaque AI models prize performance over interpretability, which makes testing difficult. However, formal statistical tests conducted on a model

safetyarxiv-cs-lg

QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models

arXiv:2607.29445v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering

TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ

researcharxiv-cs-cl

Top eight misconceptions about OpenAI’s amazing new Astra math results. 1. Expertise in one domain does not at all guarantee expertise in al…

applicationsgary-marcus--x

Top eight misconceptions about OpenAI’s amazing new Astra math results. 1. Expertise in one domain does not at all guarantee expertise in all or even most domains. There is an important, principled re

2 Aug 2026

ARES: Anomaly Recognition Model For Edge Streams

arXiv:2511.22078v2 Announce Type: replace Abstract: Many real-world scenarios involving streaming information can be represented as temporal graphs, where data flows through dynamic changes in edges o

applicationsarxiv-cs-lg

Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning

arXiv:2607.27968v1 Announce Type: new Abstract: Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privac

BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models

arXiv:2512.00807v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation. Current fairness interve

ChronoMem: Version Control and Semantic Rollback for Large Language Model Agent Memory

model-releasesarxiv-cs-cl

arXiv:2607.27773v1 Announce Type: new Abstract: LLM agents increasingly rely on long-term memory to support multi-session interaction and personalization. However, existing agent memory systems are de

Tutorials

Dynamically Scaled Activation Steering

arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat

tutorialsarxiv-cs-lg

Agents

Pramana: A Composable, Domain-Specific Backend for Empirical Networking Research

arXiv:2607.26352v1 Announce Type: cross Abstract: Networking research advances by turning hypotheses into empirical evidence, so accelerating it means reducing the lag between ideation (synthesizing a

agentsarxiv-cs-ai

Some deepseek-v4-flash 20260731 opinion review

model-releasesr-localllama

First of all, I want to apologize if it's off-topic or in the wrong format. Having tried Deepseek Flash with reasoning high on a conceptually difficult task, involving Machine Learning classifiers and

STEREODISCO: Discovering Stereotypicality in LLMs

arXiv:2607.27824v1 Announce Type: cross Abstract: LLMs encode, convey, and perpetuate stereotypes. Prior computational research focuses on a small set of semantic axes investigated in social psycholog

The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models

arXiv:2602.08159v2 Announce Type: replace-cross Abstract: When a language model asserts that 'the capital of Australia is Sydney,' does it know this is wrong? Models assert misconceptions with the sam

safetyarxiv-cs-cl

TraceCoder: Explainable and Auditable Code Generation with Position-Key Snippet Versioning

model-releasesarxiv-cs-ai

arXiv:2607.26307v1 Announce Type: new Abstract: Contemporary LLM-based coding agents produce code as black-box outputs: the rationale behind each line is hidden, the evolution of the code through benc

Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective

arXiv:2607.27660v1 Announce Type: cross Abstract: Submodular Information Measures (SIMs) have recently emerged as a powerful framework for representation learning and multimodal learning. In particula

When Robots Exchange Meaning: A Demo of Goal-Oriented Semantic Communications for Collaborative Robotics

arXiv:2607.28256v1 Announce Type: new Abstract: Collaborative robotics is a representative task-oriented 6G use-case, where communication quality should be reflected in mission execution, environment

researcharxiv-cs-ro

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

arXiv:2504.19621v2 Announce Type: replace Abstract: Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig

safetyarxiv-cs-lg

Detecting seizure onset and offset times using human intelligence: A critical-transitions-based approach

arXiv:2607.27105v1 Announce Type: cross Abstract: Most existing seizure detection algorithms require extensive pre-processing of the data and rely on heuristic or currently unexplainable machine learn

researcharxiv-cs-lg

Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach

arXiv:2607.26704v1 Announce Type: cross Abstract: Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate f

applicationsarxiv-cs-lg

ForgetBench: Benchmarking Forgetting Dynamics of Long-Term Parametric Memory in Language Models

model-releasesarxiv-cs-cl

arXiv:2607.26455v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in knowledge acquisition and reasoning, yet their ability to retain previously acquir

Global Sensitive-Based Input Shaping for UAV-Payload Precision Motion Control

arXiv:2607.26717v1 Announce Type: cross Abstract: This work presents a comprehensive analysis and design of global sensitivity-based input shapers for a 3D Unmanned Aerial Vehicle-payload system, emph

researcharxiv-cs-ro

High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption

arXiv:2607.26357v1 Announce Type: new Abstract: The problem of learning the graphical Markov blanket (MB) of a variable from data has applications in many areas such as structure learning for Bayesian

researcharxiv-cs-lg

Learning Dynamic User Personas from Implicit Interaction Streams via Iterative Refinement

arXiv:2607.26473v1 Announce Type: cross Abstract: Personalizing large language models (LLMs) to individual users is essential for improving user experience, yet existing approaches typically rely on e

applicationsarxiv-cs-cl

Multimodal fusion of visual and morphometric features for avian bone classification

arXiv:2607.26743v1 Announce Type: new Abstract: Artificial intelligence has shown considerable potential for archaeological applications, yet its use in zooarchaeology remains limited, particularly fo

Robostreet Flow: A Lightweight, Ultra-Low-Drag Electric Tractor and Four-Truck Hybrid Convoy Architecture for Minimum-Cost Point-to-Point Freight

arXiv:2607.26250v1 Announce Type: new Abstract: Line-haul trucking costs are dominated by three comparably sized components: energy, driver labor, and equipment. Most efficiency technologies address o

safetyarxiv-cs-cl

Structurally Separated Uncertainty in Supervised Latent Variable Models

arXiv:2602.11219v2 Announce Type: replace Abstract: Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated

TPD: Temporal Prior Decoupling for Text-to-Video Diffusion Models

arXiv:2607.26706v1 Announce Type: new Abstract: Text-to-video diffusion models generate temporally coherent content from natural language, yet when a prompt describes an early scene that persists whil

TraceCLIP: Recovering Local Semantics from Patch-to-CLS Contributions

arXiv:2607.26107v1 Announce Type: new Abstract: Dense vision-language understanding, including object localization, region recognition, and open-vocabulary semantic segmentation, requires associating

safetyarxiv-cs-cv

Under the Hood: Serving Kimi K3

model-releasesdigitalocean

DigitalOcean launched Kimi K3 on day 0. It’s already one of the most popular models on the platform and across the market: second most likes on Hugging Face, sixth most traffic on OpenCode. Getting a

A Path Integral Model of Cognition

arXiv:2607.24807v1 Announce Type: cross Abstract: We develop the mathematical and physical formulation of cognitive cost optimization that underlies the path-integral model of consciousness. The goal-

researcharxiv-cs-ai

Behavior-Driven Explainability

arXiv:2607.24881v1 Announce Type: new Abstract: As system complexity has vastly increased, it has become significantly more challenging for a single person or a team to fully understand all aspects of

safetyarxiv-cs-lg

Computational Extraction of Legal Causes via al-Sabr wa al-Taqsim: A Set-Theoretic Formalization for Closed Fiqh Chapters

arXiv:2607.25605v1 Announce Type: new Abstract: This paper presents a set-theoretic formalization of the classical usuli method of al-Sabr wa al-Taqsim (Examination and Division) for extracting legal

applicationsarxiv-cs-ai

EviDAG: Auditable Causal DAG Authoring with Biomedical Literature

model-releasesarxiv-cs-ai

arXiv:2607.21859v2 Announce Type: replace Abstract: Constructing causal directed acyclic graphs (DAGs) is a core step in biomedical causal analysis, yet it remains a largely manual process. Analysts m

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

arXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias re

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

model-releasesberkeley-ai-research

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new

HOME: Robust Hough-space Matching Method for Structured and Textureless Videos

arXiv:2607.25389v1 Announce Type: new Abstract: Visual front-ends for robotic localization typically rely on point-based features such as Oriented FAST and Rotated BRIEF (ORB), which frequently fail i

Industry

The Time Traveler’s Satchel - Fictional photographs from Human History, created with ChatGPT Sol5.6 Max Work Mode (Part 1)

Quick clarification before opening the bag: every image here is fictional and AI-generated. These are not real archival discoveries or claims about hidden history. This series grew out of two earlier

industryr-chatgpt

Local Ai

Understand Kimi K3 from first principles: a recommended order for anyone trying to understand this beast

Everyone is talking about Kimi K3, but if you jump straight into the technical report, you’ll quickly realize it’s standing on years of research -- just like any breakthrough is! If you want to unders

local-air-localllama

WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders

arXiv:2607.25763v1 Announce Type: cross Abstract: This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model fo

Why Public Service AI Governance Frameworks Risk Failing in the Age of General-Purpose AI: Lessons from Policing

arXiv:2607.25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressur

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r

Hardware

A didactical-driven teacher assistant for a dimensional modeling course

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

hardwarearxiv-cs-ai

A scalable online machine learning approach for Stock Recommendation

arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e

applicationsarxiv-cs-ai

Adapter Merging Reactivates Latent Reasoning Traces: A Mechanism Analysis

arXiv:2601.18350v5 Announce Type: replace-cross Abstract: Large language models fine-tuned via a two-stage pipeline (domain adaptation followed by instruction alignment) can exhibit non-trivial interf