Search: “evaluation”

llm-openai-decisions 0.1a0

model-releasessimon-willison

Release: llm-openai-decisions 0.1a0 OpenAI released their new Jev-style Decisions API, as previously announced at last week's DevDay. Since I already have an llm-typesafe plugin for talking to Jev, I

Local Ai

Localization Lens for Improving Medical Vision-Language Models

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2610.04502v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) have demonstrated strong capabilities in clinical tasks. However, they often struggle to understand anatomical

local-aiarxiv-cs-cv

6 Oct 2026

Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks becaus

Long-MDR: Long-Context Reinforcement Learning for Multimodal Deep-Research Agents

arXiv:2610.05195v1 Announce Type: new Abstract: The next generation of multimodal research agents must reason over long-lived research histories rather than short model completions. During a single ta

Local Ai

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

arXiv:2610.05023v1 Announce Type: new Abstract: We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image r

local-aiarxiv-cs-cv

Lossy Compression of PDE Training Inputs: Field Reconstruction Error Does Not Order the Cost to a Trained Operator

arXiv:2610.06095v1 Announce Type: new Abstract: Operator-learning benchmarks are stored at full precision and have grown to terabyte scale. Rate-distortion theory says how many bits the stored field n

LyapuFlow: Controlling Generative Flows with Lyapunov Feedback for Inverse Problems

arXiv:2610.04326v1 Announce Type: new Abstract: Pretrained flow models are now widely used as generative priors in science and vision, where inference-time guidance enables test-time constraints witho

M^2-Occ: Resilient 3D Semantic Occupancy Prediction for Autonomous Driving with Incomplete Camera Inputs

arXiv:2603.09737v2 Announce Type: replace Abstract: Semantic occupancy prediction enables dense 3D geometric and semantic understanding for autonomous driving. However, existing camera-based approache

Machine learning modeling of hit-into-play probability and quantification of pitch sequence effects

arXiv:2606.17345v2 Announce Type: replace Abstract: Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on improving predictive performance for

MAGEFormer: Learning Metric-Consistent Representations for Anisotropic CT Segmentation

arXiv:2610.04036v1 Announce Type: new Abstract: Vision Transformers (ViTs) have shown strong performance in volumetric segmentation, but their effectiveness on clinical CT is limited by an isotropic E

ManifoldCache: Training-Free Diffusion Acceleration via Constraint Manifold Caching

arXiv:2610.04510v1 Announce Type: cross Abstract: Diffusion models for structured scientific generation must produce samples satisfying hard geometric constraints imposed by physics, chemistry, or bio

MarvisNav: Making Memory Visible on Route Choices for Zero-Shot Object Navigation

arXiv:2610.06510v1 Announce Type: new Abstract: When searching for an object, people choose their next move by considering both likely target locations and places already explored. The current view ca

MDKeyChunker: What Does One LLM Call per Chunk Buy for Markdown Retrieval?

arXiv:2603.23533v3 Announce Type: replace-cross Abstract: Markdown carries structure a parser reads for free: headers, section paths, and block boundaries. Many RAG pipelines also spend LLM calls per

MedAD-R1: Consistency-Reinforced Policy Optimization for Interpretable Medical Anomaly Detection

arXiv:2602.01081v2 Announce Type: replace Abstract: Medical Anomaly Detection (MedAD) offers a promising direction for medical image analysis with Large Multimodal Models (LMMs). However, progress is

MemLeak: Cross-User Semantic Leakage in Multi-Tenant AI Agent Memory

arXiv:2610.04195v1 Announce Type: cross Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface f

Memoria 1.0.0 — a local, model-agnostic memory system for LLMs

model-releasesr-localllama

I’ve been building this for a long fucking time, and tonight I finally released Memoria 1.0.0. I built it because I actually wanted to use it. I wanted a real memory layer for local LLM applications t

Memory-State Critic for Asymmetric Actor-Critic with Application to Vision-Based Pursuit-Evasion

arXiv:2610.03830v1 Announce Type: new Abstract: In partially observable Markov decision processes, the optimal policy generally depends on the history of observations and past actions. Asymmetric acto

MeSD: Multi-Evidence Self-Distillation for VideoLLM

arXiv:2610.06342v1 Announce Type: new Abstract: While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-lev

Mistral Large 4 against the field: efficiently reasoning over diverse complex challenges. CTF speedrun: 19 challenges, with tool calls and s…

model-releasesmistral-ai--x

Mistral Large 4 against the field: efficiently reasoning over diverse complex challenges. CTF speedrun: 19 challenges, with tool calls and solve times grounded in actual runs. It solved 18 of the 19.

Mistral Large 4 is one of the world's strongest AI models for cybersecurity.

model-releasesmistral-ai--x

Mistral AI announced that its new model, Mistral Large 4, is among the world's most powerful AI systems specifically designed for cybersecurity tasks. The tweet shared on October 6, 2026 highlights th

MoCAR: Motion-code Coordinate-aware AutoRegression for Continuous Trajectory Forecasting

arXiv:2610.06210v1 Announce Type: new Abstract: Autoregressive generation is natural for language, where predicted tokens can be directly reused as the next prediction state, but trajectory forecastin

Monitorability Disposition in Large Reasoning Models

arXiv:2610.04914v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of large reasoning models (LRMs) is a common way to detect misbehavior in real-world practice. However, current

MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity

arXiv:2610.06378v1 Announce Type: new Abstract: The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video

Mulligan: Performance-Guided Data Collection for Efficient On-Robot Learning

arXiv:2610.05882v1 Announce Type: cross Abstract: Learning from human demonstrations is a reliable way to teach robots new tasks, but the gains from each additional demonstration shrink as the policy

MuViSeg: Multi-View Segment Correspondences from Dense Geometry Priors

arXiv:2607.17938v2 Announce Type: replace Abstract: Object-level mapping and topological navigation reason about whole objects, yet the correspondences they rely on are computed over keypoints or pixe

Tutorials

Neural Bayesian Filtering

arXiv:2510.03614v2 Announce Type: replace Abstract: Sequential estimation under partial observability requires tracking beliefs that may be high-dimensional, multimodal, and non-Gaussian. Classical Ba

tutorialsarxiv-cs-lg

NM-LIO: Multiple LiDAR-Inertial Odometry Addressing LiDAR Measurement Noise Discrepancy

arXiv:2610.04551v1 Announce Type: new Abstract: Multiple LiDAR-inertial odometry methods have been widely applied in robotic applications owing to their enhanced accuracy and reliability. However, ado

researcharxiv-cs-ro

Now You Feel It, Now You See Me: Digital-Twin-based Teleoperation Interface for Dexterous Manipulation

arXiv:2610.05081v1 Announce Type: new Abstract: Teleoperation is becoming increasingly important for collecting high-quality demonstrations to teach robots dexterous manipulation skills. For dexterous

researcharxiv-cs-ro

Tutorials

OCL-PDE: A Generative Framework for PDE Inverse Problems with Observation-Complementary Latents

arXiv:2610.06259v1 Announce Type: new Abstract: Partial differential equation (PDE) inverse problems are often ill-posed, making fine-scale details difficult to recover. We address this problem by int

tutorialsarxiv-cs-lg

One-Cycle Fault Classification and Faulted-Line Identification on the PROTECT-90 Dataset: An Initial Application Benchmark

arXiv:2610.04155v1 Announce Type: cross Abstract: Open electromagnetic-transient datasets are beginning to make reproducible learning-based protection studies possible, but the practical use of these

One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipeline

arXiv:2610.06852v1 Announce Type: new Abstract: Pipeline figures in ML papers must be repurposed across many canvases, including paper columns, 16:9 slides, portrait posters, 1:1 social teasers, 9:16

One Tile, Multiple Instances: Rethinking MIL for Sparse Diagnostic Evidence

arXiv:2610.04853v1 Announce Type: new Abstract: In weakly supervised Whole Slide Image (WSI) classification, feature extractors typically compress each image tile into a single global embedding. Conse

researcharxiv-cs-cv

Only Project Once: Projection-Adaptive Loss for Exact Constraint Satisfaction

arXiv:2610.04572v1 Announce Type: new Abstract: Precise constraint satisfaction is a prerequisite to deploying learned models in many areas, motivating methods that repair raw neural predictions with

Local Ai

Optimal Control with Learned Critics under Unmodeled State Dependencies

arXiv:2610.05359v1 Announce Type: new Abstract: Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analy

local-aiarxiv-cs-ro

PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents

arXiv:2610.05732v1 Announce Type: new Abstract: LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons. Existing methods provide limited support f

Agents

Pareto-Dominant Clarification: Post-Training Coding LLMs via PPO-Lagrangian Budget Constraints

arXiv:2610.04089v1 Announce Type: new Abstract: Coding agents operating under ambiguous instructions or user prompts must decide whether to ask clarifying questions or attempt a solution directly. Whi

agentsarxiv-cs-lg

Pareto-Improving Adversarial Attacks with Primal-Dual Regularization

arXiv:2610.04652v1 Announce Type: new Abstract: Transferable adversarial attacks are arguably the most practical black-box threat model. Under the same perturbation budget, stronger transfer attacks a

PatternDex: Learning Interaction Patterns to Guide Reinforcement Learning of Bimanual Dexterous Manipulation of Articulated Objects

arXiv:2610.04765v1 Announce Type: new Abstract: In this paper, we develop a method that enables bimanual dexterous hands to manipulate articulated objects with a high success rate without suffering fr

PB-STDG: A Prediction-Based Short-Term Decentralized Greedy Guidance Algorithm for a Drone Road System

arXiv:2610.05122v1 Announce Type: new Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) or drones have been increasingly adopted in urban environments for applications such as parcel delivery

PermVLA: Factorization Order as a Regularizer for VLA Learning

arXiv:2610.04659v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies commonly learn action chunks through a fixed left-to-right (LTR) factorization, although the same expert traject

PerturBot: Breaking Shortcut Priors in Vision-Language-Action Models with Perturbative Training

arXiv:2610.04616v1 Announce Type: cross Abstract: A vision--language--action (VLA) policy can complete complex tasks while ignoring the evidence that should determine its actions. An object held near

PhaseMatcher: Autoregressive Phase-Set Identification with Spectral Decomposition

arXiv:2610.05844v1 Announce Type: cross Abstract: Recovering complete phase sets from powder X-ray diffraction (PXRD) is challenging when weak-phase peaks overlap stronger signals. A natural strategy

Applications

Physics-aware Masked Diffusion-based Flood Simulation for Urban Fisheye Disaster Detection

arXiv:2607.15527v2 Announce Type: replace Abstract: Physical simulations that predict the behavior of urban disasters, such as climate-related flooding, play a crucial role in disaster prevention and

applicationsarxiv-cs-cv

Physics-Informed but Not Physics-Consistent: Error Geometry and Subspace Projection for Neural AC Power Flow

arXiv:2610.05959v1 Announce Type: new Abstract: Recent neural power-flow solvers, including emerging foundation models, achieve accurate voltage predictions, yet such accuracy does not necessarily imp

Physics-informed GNN for medium-high voltage AC power flow with edge-aware attention and line search correction operator

arXiv:2509.22458v3 Announce Type: replace Abstract: Physics-informed graph neural networks (PIGNNs) have emerged as fast AC power-flow solvers that can replace the classic NewtonRaphson (NR) solvers,

PIT-GCL: Protein Interaction using Topological Graph Contrastive Learning

arXiv:2610.04850v1 Announce Type: new Abstract: Protein binding prediction is central to target identification, therapeutic binder design, and large scale screening, yet remains challenging because bi

PixReenact: Pixel-Conditioned Causal Video Diffusion for Streaming Head-Avatar Reenactment

arXiv:2610.05233v1 Announce Type: new Abstract: Streaming head-avatar reenactment aims to animate a reference image according to a live driving video, requiring robust motion transfer, long-term ident

Planning for Change: Reinforcement Learning Combined with Bounded Extremum Seeking for Robotic Control under Distribution Shift

arXiv:2604.01142v2 Announce Type: replace-cross Abstract: Reinforcement learning has shown strong performance in robotic manipulation, but learned policies often degrade in performance when test condi