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arXiv:2604.07269v2 Announce Type: replace Abstract: Clinical expertise improves not only by acquiring medical knowledge, but by accumulating experience that yields reusable diagnostic patterns. Recent

agentsarxiv-cs-cl

Agents

Kimi K2.5: Visual Agentic Intelligence

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DGX agent

arXiv:2602.02276v2 Announce Type: replace-cross Abstract: We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint op

agentsarxiv-cs-ai

10 Aug 2026

KnifeHunter: Structured Local Representation Learning for Fine-Grained Knife Image Retrieval in Law Enforcement

arXiv:2608.07057v1 Announce Type: new Abstract: Knife-enabled violence presents a major public safety challenge, and law enforcement agencies require scalable tools for catalogue-level knife identific

safetyarxiv-cs-cv

Applications

KNOWPLAN: Knowledge-Driven AI Agents for Smart Degree Pathway Planning

arXiv:2608.06530v1 Announce Type: new Abstract: Planning a degree from official university sources requires solving two problems in order. The institution's curriculum must first be reconstructed from

applicationsarxiv-cs-ai

KReF: Training-Free Retrieval for Long-Term Time-Series Forecasting and Predictive Uncertainty

arXiv:2608.06748v1 Announce Type: cross Abstract: Probabilistic long-term time-series forecasting commonly relies on trained models. Training-free conformal methods typically construct intervals aroun

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

Learning Fault-Tolerant Locomotion with Adaptive Gait Timing

model-releasesarxiv-cs-lg

arXiv:2608.07328v1 Announce Type: cross Abstract: Hardware failures require legged robots to rapidly reorganize coordination and gait timing to maintain stability and mobility. This is particularly ch

Learning in Deep Networks under Dale's Constraint

arXiv:2608.06963v1 Announce Type: new Abstract: Biologically plausible learning models aim to explain how neural circuits can implement effective learning under the constraints of real neurons. Althou

Applications

Learning Ordinal Degradation Representations with Textual Priors for Diffusion-Based Blind Image Super-Resolution

arXiv:2512.10340v2 Announce Type: replace Abstract: Blind image super-resolution (Blind SR) has achieved remarkable perceptual quality via generative priors. However, lacking clear degradation represe

applicationsarxiv-cs-cv

Learning Suffers More Than the Policy Class Under Partial Observability: A Closed-Form Analysis

arXiv:2608.07228v1 Announce Type: new Abstract: When a reinforcement learning agent cannot observe the full state, we usually blame its policies: it cannot see enough to represent a good one. We show

safetyarxiv-cs-lg

Tutorials

Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Prunin

arXiv:2608.06411v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance across diverse vision-language tasks, but their efficiency is limited by the cost of

tutorialsarxiv-cs-ai

Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion

arXiv:2509.06296v2 Announce Type: replace-cross Abstract: Traditional on-policy reinforcement learning (RL) controllers for quadrupedal locomotion often suffer from low data efficiency, requiring mill

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv:2509.16462v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used in high-stakes decision-making systems, where biased predictions can reinforce social and economi

safetyarxiv-cs-cl

LifelongCrossNav: Persistent 3D Semantic Memory for Cross-Floor Multi-Object Navigation

arXiv:2608.07079v1 Announce Type: cross Abstract: Object-goal navigation has made substantial progress in semantic perception and exploration, yet persistent memory for multi-object navigation and cro

LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting

arXiv:2608.06765v1 Announce Type: new Abstract: Continuous-time dynamic graph models predict future links by compressing past interactions into neural states. Although effective for forecasting, this

researcharxiv-cs-ai

Tutorials

Limit Points of Reflow with Minibatch Optimal Transport

arXiv:2608.07042v1 Announce Type: cross Abstract: Rectified flows, also called flow matching or stochastic interpolants, are generative models that learn a time-dependent vector field steering a proba

tutorialsarxiv-cs-lg

Literally for years I have been warning everyone: @GaryMarcus, December, 2022: “GPT-4 will still, like its predecessors, be a bull in a chin…

model-releasesgary-marcus--x

Literally for years I have been warning everyone: @GaryMarcus, December, 2022: “GPT-4 will still, like its predecessors, be a bull in a china shop, reckless and hard to control.” @GaryMarcus, November

LitTraceQA: A Benchmark for Multi-Stage Grounding and Verification in Scientific Question Answering

arXiv:2608.07370v1 Announce Type: new Abstract: Scientific literature is increasingly used as a knowledge source for language models, retrieval-augmented generation systems, and research assistants, b

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers

arXiv:2608.06867v1 Announce Type: new Abstract: No single large language model (LLM) is optimal across all queries and budget constraints, making model routing essential for cost-effective deployment.

LMM Modality Transfer: A Pre-requisite for Autonomous GIS Agents

arXiv:2608.06948v1 Announce Type: new Abstract: AI models are becoming increasingly adept at understanding and processing spatial information, thereby facilitating agentic problem-solving in spatial t

Local Epistemic Uncertainty Guided Active Sampling for Plug-and-play Diffusive Image Restoration

arXiv:2608.06981v1 Announce Type: new Abstract: Diffusion models have demonstrated remarkable effectiveness in image restoration tasks. However, when guiding image reconstruction, existing Diffusion M

researcharxiv-cs-cv

Long-Horizon Agent Trajectory Attribution: A Unified Benchmark and Fine-Grained Annotation Framework

arXiv:2608.06909v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate through long-horizon trajectories involving user instructions, tool use, external observations, a

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

Lost in Interpolation: Why Predictive Feedback Fails in Diffusion Language Models

arXiv:2608.06529v1 Announce Type: new Abstract: Soft-masking accelerates the convergence of Masked Diffusion Language Models (MDLMs). Existing formulations build this blend with linear interpolation (

LSEAD: A Privacy-Preserving LLM-Based Speech Analysis Framework for Early Alzheimer's Disease Screening

arXiv:2608.07378v1 Announce Type: cross Abstract: Early diagnosis of Alzheimer's disease (AD) is critical for enabling timely interventions that may slow disease progression and improve patient outcom

LyEvO: Lyapunov-Guided Evolutionary Optimization for Safe and Robust Sim-to-Real Policy Learning

arXiv:2608.06481v1 Announce Type: cross Abstract: Training controllers that are safe and robust in simulation, and systematically assessing their readiness for real-world deployment, remain key challe

Local Ai

M2-SMap: Memory-Efficient Semantic Mapping with Hierarchical Multi-Model Representation

arXiv:2608.07074v1 Announce Type: new Abstract: Dense point cloud maps, as a typically used mapping representation, are difficult to deploy on resource-constrained robots because their memory consumpt

local-aiarxiv-cs-ro

MAC: A Conversion Rate Prediction Benchmark Featuring Labels Under Multiple Attribution Mechanisms

arXiv:2603.02184v2 Announce Type: replace-cross Abstract: Multi-attribution learning (MAL), which enhances model performance by learning from conversion labels yielded by multiple attribution mechanis

Machine Learning-Based Inter-Crystal Scatter Recovery for Ultra-High Resolution PET Imaging

arXiv:2608.07155v1 Announce Type: new Abstract: Inter-crystal scatter (ICS) events pose a significant challenge in ultrahigh- resolution positron emission tomography (UHR-PET), especially as detector

MaskFlow: Precise, Consistent and Seamless Regional Image Editing

arXiv:2608.06929v1 Announce Type: cross Abstract: Regional image editing has attracted considerable attention for its spatial controllability. Although instruction-based and mask-reference-based editi

Mathematical Principles and Experimental Discoveries of the Emergence of Symbolic Patterns in Artificial Neural Networks

arXiv:2608.06839v1 Announce Type: new Abstract: Artificial Neural networks (ANNs) are often treated as black-box models, making explainability a central challenge in deep learning. Many engineering me

Local Ai

MAUPITI: On-Device Prototype-Based Learning on a Smart Infrared Sensor

arXiv:2608.07192v1 Announce Type: new Abstract: Low-resolution infrared (IR) array sensors represent an interesting solution for privacy-preserving human sensing in embedded systems. In this letter, w

local-aiarxiv-cs-lg

Mean-square and sublinear convergence of a stochastic proximal point algorithm in metric spaces of nonpositive curvature

arXiv:2510.10697v2 Announce Type: replace-cross Abstract: We define a stochastic variant of the proximal point algorithm in the general setting of nonlinear Hadamard spaces for approximating zeros of

Measurements Automatically Extracted from Zero Echo Time MRI Using Deep Learning Image Segmentation and Geometric Modeling Agree with Expert Manual Readings

arXiv:2608.07368v1 Announce Type: cross Abstract: Computed tomography (CT) remains the reference for 3D osseous morphometry in femoroacetabular impingement (FAI) but requires ionizing radiation and ma

researcharxiv-cs-ai

Measuring Concept Content in Text from LLM Activations: ESG Evidence from Concept Vectors and Linear Probes

arXiv:2608.07208v1 Announce Type: cross Abstract: Existing measures of how much a text is about a concept read the surface of the text: dictionary word shares, topic proportions, embedding similaritie

researcharxiv-cs-ai

Measuring the Cross-Lingual Comprehension Gap: How the language of the evidence shapes what language models understand

arXiv:2608.06506v1 Announce Type: new Abstract: Language models are often evaluated as though capabilities demonstrated in English remain equally available when the same content is presented in other

researcharxiv-cs-cl

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents

arXiv:2608.07068v1 Announce Type: new Abstract: Long-horizon agents accumulate growing contexts during interaction, impairing performance and stability. Compact memory mitigates this problem by compre

MemPrism: Task-Conditioned Relational Memory Views for Long-Horizon Agents

arXiv:2608.06745v1 Announce Type: new Abstract: Long-horizon agents rely on memory to reuse experiences, yet existing memory systems often assume that evidence can be directly consumed through a fixed

MemWM: Memory-Augmented Text-Based World Model

arXiv:2608.07107v1 Announce Type: new Abstract: World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent ne

Meta released Muse Glimmer 30B: multimodal model for your Claw/Pi setups 🔥 we tested and fine-tuned the model for you, and shipped day-0 su…

model-releasesgeorgi-gerganov--x

Meta released Muse Glimmer 30B: multimodal model for your Claw/Pi setups 🔥 we tested and fine-tuned the model for you, and shipped day-0 support in transformers and llama.cpp, including DFlash for 2-4

Meta releases open-source Muse Glimmer model with 30B parameters

model-releasessiliconangle

Meta Platforms Inc. today released Muse Glimmer, an open-source language model that can run on personal computers. The company also published a lengthy essay penned by Chief Executive Officer Mark Zuc

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence …

model-releasesyann-lecun--x

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta

Hardware

Meta says Muse Glimmer has 30B parameters and is 'small enough' to need only one GPU; Meta plans a $1B fund to invest in US communities near its data centers (Vlad Savov/Bloomberg)

Vlad Savov / Bloomberg: Meta says Muse Glimmer has 30B parameters and is “small enough” to need only one GPU; Meta plans a $1B fund to invest in US communities near its data centers — Meta Platforms I

hardwaretechmeme

MI-MIDI: Mechanistic Interpretability of Text-to-MIDI Generation Models via Probing, Lenses and Steering

arXiv:2608.06638v1 Announce Type: cross Abstract: Mechanistic interpretability of music generation has concentrated on audio models, leaving symbolic models largely unexplored. We analyze two public t

Local Ai

MiCoPro: End-to-End Mixed Precision HW/SW Co-design with HW-aware Proxy Model

arXiv:2608.06916v1 Announce Type: new Abstract: Quantized Neural Networks~(QNN) with low-bitwidth data have proven promising in efficient storage and computation on edge devices. To mitigate accuracy

local-aiarxiv-cs-lg

MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records

arXiv:2608.06430v1 Announce Type: new Abstract: Learning from Electronic Health Records (EHRs) has gained significant attention due to its potential to improve clinical prediction. However, effective

Mind the Gap: A Dual Knowledge Graph Framework for Unified Multi-task User Intent Inference

arXiv:2608.06752v1 Announce Type: new Abstract: This paper proposes DKG-MTI, a dual knowledge graph framework for unified multi-task user intent inference from online travel reviews. Existing approach

Minimal Ingredients for Reward Assignment from Expert Demonstrations

arXiv:2506.06793v2 Announce Type: replace-cross Abstract: Reward assignment from scarce demonstrations is a key challenge in both offline and online imitation learning. A common and intuitive strategy