All entries

It's crazy that this is even possible today. It inspired me to build my own self-improving coding agent with simple read, write, bash,... I …

It's crazy that this is even possible today. It inspired me to build my own self-improving coding agent with simple read, write, bash,... I already used the coding agent to build an entire production-

agentsdair-ai--x

Safety

It's Not Always Sycophancy: Measuring LLM Conformity as a Function of Epistemic Uncertainty

DGX agent

arXiv:2605.27288v1 Announce Type: cross Abstract: Large language models (LLMs) are known to abandon their initial stance to conform to user pushback. While prior research largely attributes this behav

safetyarxiv-cs-ai

27 May 2026

It's Not the Capability: Harness Sensitivity Is Non-Monotone Across LLM Agent Tiers

arXiv:2605.26731v1 Announce Type: new Abstract: A prevalent assumption in LLM agent deployment holds that more structured harnesses universally improve reliability, and that higher-capability models n

Jailbreak susceptibility prediction and mitigation via the behavioral geometry of models

arXiv:2605.26409v1 Announce Type: cross Abstract: Evaluating and mitigating a generative system's susceptibility to jailbreak attacks is critical to its safe deployment. Given the number of deployable

safetyarxiv-cs-ai

Hardware

Jensen Huang says Nvidia is spending 100B-150B annually on its Taiwan supply chain, up from 10B-15B four years ago, and will boost its Taiwan staff to 4,000 (Nikkei Asia)

Nikkei Asia: Jensen Huang says Nvidia is spending 100B-150B annually on its Taiwan supply chain, up from 10B-15B four years ago, and will boost its Taiwan staff to 4,000 — TAIPEI — Nvidia is now spend

hardwaretechmeme

jesus, qwen3-tts is FANTASTIC. going for full local stt/tts/llm with parakeet, qwen3-tts, and gemma 4 via llama.cpp for my little robot. exc…

model-releasesclem-delangue--x

jesus, qwen3-tts is FANTASTIC. going for full local stt/tts/llm with parakeet, qwen3-tts, and gemma 4 via llama.cpp for my little robot. excite, excite! https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B

Hardware

JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search

arXiv:2605.26636v1 Announce Type: cross Abstract: We introduce JetViT, a novel family of hybrid-architecture Vision Transformer (ViT) models that match the accuracy of state-of-the-art full-attention

hardwarearxiv-cs-ai

JLT: Clean-Latent Prediction in Latent Diffusion Transformers

arXiv:2605.27102v1 Announce Type: new Abstract: Flow matching with clean-data prediction has shown that regressing the clean point can exploit low-dimensional structure more effectively than predictin

researcharxiv-cs-cv

JobBench: Aligning Agent Work With Human Will

arXiv:2605.26329v1 Announce Type: new Abstract: Current benchmarks for occupational AI agents are scoped primarily by economic values, telling a replacement story. We introduce JobBench, which evaluat

Tutorials

Joint 2D-3D Segmentation and Association in Street-level Imaging

arXiv:2605.26725v1 Announce Type: new Abstract: Accurate interpretation of street-level imagery is essential for large-scale urban mapping and the creation of Spatial Digital Twin (SDT) environments.

tutorialsarxiv-cs-cv

Joint Instance Segmentation and Geometric Attribute Regression for Roof Structures in Aerial Imagery

arXiv:2605.26370v1 Announce Type: new Abstract: We present a method for jointly predicting instance-level roof segment masks together with three continuous geometric attributes -- building height, roo

researcharxiv-cs-cv

JuICE: A Benchmark for Evaluating LLM-Judge in Identifying Cultural Errors

arXiv:2605.26955v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed to users around the world, they are integrated into everyday tasks across diverse cultural c

Kan Extension Transformers: A Categorical Unification of Attention, Diffusion, and Predict-Detach Self-Conditioning

arXiv:2605.27259v1 Announce Type: new Abstract: We propose Kan Extension Transformers (KETs) as a unifying categorical framework for a diverse group of Transformer implementations. The core claim is t

researcharxiv-cs-lg

Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation

arXiv:2511.14993v3 Announce Type: replace-cross Abstract: This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis.

KARMA: Karma-Aligned Reward Model Adaptation

arXiv:2605.26738v1 Announce Type: new Abstract: Human communication depends on implicit social signals where effectiveness is shaped by tone, context, and conversational norms rather than semantic con

safetyarxiv-cs-cl

Knowledge Graphs as the Missing Data Layer for LLM-Based Industrial Asset Operations

arXiv:2605.26874v1 Announce Type: cross Abstract: LLM-based agents for industrial asset operations show limited accuracy when reasoning over flat document stores. AssetOpsBench (KDD 2026) establishes

Local Ai

KREA 2 Image is now a Partner Node in ComfyUI KREA's first foundation image model — trained from scratch — with tunable creativity, style re…

KREA 2 Image, KREA's foundational image generation model trained from scratch with adjustable creativity and style parameters, has been integrated as a partner node within ComfyUI. This integration al

local-aicomfyui--x

Krea is now built in to Hermes Agent as an image generation API provider, allowing your agent to use Krea 2: a new foundation model trained …

model-releasesnous-research--x

Krea is now built in to Hermes Agent as an image generation API provider, allowing your agent to use Krea 2: a new foundation model trained from scratch to balance aesthetic quality and fine control,

KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models

arXiv:2605.26947v1 Announce Type: new Abstract: Kazakh is underrepresented in resources for evaluating the safety behavior of large language models. We present KZ-SafetyPrompts, a Kazakh prompt datase

safetyarxiv-cs-cl

L-Learning : A Lyapunov-Based Approach Leveraging Lagrangian Mechanics for Efficient and Stable Robot Tracking

arXiv:2605.26648v1 Announce Type: new Abstract: This paper presents L-Learning, a novel data-driven control framework for robotics that integrates Lyapunov stability theory with Lagrangian mechanics t

researcharxiv-cs-ro

L2Rec: Towards Dual-View Understanding of LLMs for Personalized Recommendation

arXiv:2605.26717v1 Announce Type: cross Abstract: Adapting large language models (LLMs) for personalized recommendation requires aligning their general-purpose capabilities with user-specific preferen

LAD-VF: LLM-Automatic Differentiation Enables Fine-Tuning-Free Robot Planning from Formal Methods Feedback

arXiv:2509.18384v2 Announce Type: replace Abstract: Large language models (LLMs) can translate natural language instructions into executable action plans for robotics, autonomous driving, and other do

safetyarxiv-cs-ro

LaRe: Latent Refocusing for Multimodal Reasoning

arXiv:2511.02360v4 Announce Type: replace-cross Abstract: Chain of Thought (CoT) reasoning enhances logical performance by decomposing complex tasks, yet its multimodal extension faces a trade-off. Th

Large Language Model-Powered Query-Driven Event Timeline Summarization in Industrial Search

arXiv:2605.27066v1 Announce Type: new Abstract: Understanding how events evolve over time is essential for search engines handling queries about trending news. We present QDET (Query-Driven Event Time

Last Week in AI #341 - Musk loses to OpenAI, Google's IO updates, OpenAI solves Erdős

model-releaseslast-week-in-ai

This newsletter episode covers major AI developments including Elon Musk's legal loss against OpenAI, updates announced at Google's I/O conference, and OpenAI's achievement in solving the Erdős discre

Latent Recurrent Transformer: Architecture Exploration, Training Strategies, and Scaling Behavior

arXiv:2605.26797v1 Announce Type: cross Abstract: We study Latent Recurrent Transformer (LRT), a lightweight augmentation of autoregressive transformers that reuses a high-level source-layer hidden st

Tools

latent space pod is still very underrated, especially on the applied side of things glad that they have kept it very high signal one of the …

latent space pod is still very underrated, especially on the applied side of things glad that they have kept it very high signal one of the few pods i listen to while working out and I always find mys

toolsswyx--x

LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation

arXiv:2605.26612v1 Announce Type: new Abstract: Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization meth

researcharxiv-cs-cl

Local Ai

LDP-Slicing: Local Differential Privacy for Images via Randomized Bit-Plane Slicing

arXiv:2603.03711v3 Announce Type: replace Abstract: Local Differential Privacy (LDP) is the gold standard trust model for privacy-preserving machine learning by guaranteeing privacy at the data source

local-aiarxiv-cs-cv

Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2505.21285v4 Announce Type: replace Abstract: This work proposes a framework LGKDE that learns kernel density estimation for graphs. The key challenge in graph density estimation lies in effecti

LearnedCache: An eBPF-Integrated Perceptron-Based Eviction Policy for the Linux Page Cache

arXiv:2605.26168v1 Announce Type: cross Abstract: Linux is the foundation of the digital age, accounting for the majority of the cloud and mobile OS markets. Any device that runs Linux uses the Linux

Learning Compositional Symbolic Task Rules from Demonstrations with Inductive Logic Programming

arXiv:2605.26828v1 Announce Type: new Abstract: Learning from Demonstration~(LfD) should capture not only how a task is executed, but also its high-level task structure that explains the demonstrated

agentsarxiv-cs-ro

Learning Dynamic Graph Representations through Timespan View Contrasts

arXiv:2605.27063v1 Announce Type: new Abstract: The rich information underlying graphs has inspired further investigation of unsupervised graph representation. Existing studies mainly depend on node f

Tutorials

Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences

arXiv:2605.26850v1 Announce Type: new Abstract: Learning an energy-based model from data samples is a central problem in machine learning. Many recent and popular methods, such as denoising score matc

tutorialsarxiv-cs-lg

Learning GUI Grounding with Spatial Reasoning from Visual Feedback

arXiv:2509.21552v2 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) grounding is commonly framed as a coordinate prediction task -- given a natural language instruction, generate

agentsarxiv-cs-cl

Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data

arXiv:2605.26271v1 Announce Type: cross Abstract: We study a nonlinear factor model in which observed responses depend on low-rank latent factors through an unknown monotone link function. This settin

researcharxiv-cs-lg

Learning Reference-Guided Exposure Correction with Hybrid Illumination Characteristics

arXiv:2605.26729v1 Announce Type: new Abstract: We present HICNet, a reference-guided exposure correction framework. A lightweight, content-agnostic encoder distills each image into a compact illumina

researcharxiv-cs-cv

Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments

arXiv:2605.27209v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have facilitated the widespread deployment of LLMs as interactive agents capable of reasoning, planning,

agentsarxiv-cs-ai

Learning to Adapt SFT Data for Better Reasoning Generalization

arXiv:2605.26924v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress, with post-training playing a crucial role in enhancing their reasoning capabilities. Amo

researcharxiv-cs-cl

Learning to Balance Motor Thermal Safety and Quadrupedal Locomotion Performance with Residual Policy

arXiv:2605.27046v1 Announce Type: new Abstract: Motor thermal management is often overlooked in the context of electrically-actuated robots, particularly legged robots, but motor overheating is a key

safetyarxiv-cs-ro

Tutorials

Learning to Diagnose and Correct Errors: Towards Moral Sensitivity Acquisition in Large Language Models

arXiv:2601.03079v4 Announce Type: replace Abstract: Moral sensitivity is the most fundamental capability underlying human moral competence. Although many approaches aim to align large language models

tutorialsarxiv-cs-cl

Learning to Orchestrate Agents under Uncertainty

arXiv:2605.27073v1 Announce Type: new Abstract: Adaptive orchestration of heterogeneous agents requires making sequential delegation decisions under uncertain and evolving agent behaviour, e.g., coord

Learning to Predict Future-Aligned Research Proposals with Language Models

arXiv:2603.27146v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist ideation in research, but evaluating the quality of LLM-generated research proposals re

Learning to Reason Efficiently with Discounted Reinforcement Learning

arXiv:2510.23486v2 Announce Type: replace Abstract: Large reasoning models (LRMs) often consume excessive tokens, inflating computational cost and latency. More broadly, in goal reaching sequential de

Learning When to Think While Listening in Large Audio-Language Models

arXiv:2605.27190v1 Announce Type: cross Abstract: Recent advances in Large Audio-Language Models (LALMs) have made real-time, streaming spoken interaction increasingly practical. In this setting, reas

LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems

arXiv:2512.01556v3 Announce Type: replace Abstract: Foundation models often generate unreliable answers, while heuristic uncertainty estimators fail to fully distinguish correct from incorrect outputs

researcharxiv-cs-ai

Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data

arXiv:2601.12809v2 Announce Type: replace-cross Abstract: Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whether such understanding is truly acquired,

researcharxiv-cs-ai

Applications

LELA: An End-to-end LLM-based Entity Linking Framework with Zero-shot Domain Adaptation

arXiv:2605.26956v1 Announce Type: new Abstract: Entity linking is a key component of many downstream NLP systems, yet existing approaches are often tied to the specific target knowledge bases and doma

applicationsarxiv-cs-ai