All entries

KaRMA: A Kinematic Metric for Fine Manipulation Ability in Robotic Hands

arXiv:2605.15548v1 Announce Type: new Abstract: Traditional robotic hand metrics focus on static properties such as workspace, manipulability, and grasp stability. However, these metrics do not direct

researcharxiv-cs-ro

Lagrangian Flow Matching: A Least-Action Framework for Principled Path Design

DGX agent

arXiv:2605.15419v1 Announce Type: new Abstract: Flow matching trains a neural velocity field by regression against a target velocity associated with a prescribed probability path connecting a simple i

researcharxiv-cs-lg

18 May 2026

Lamarckian Inheritance in Dynamic Environments: How Key Variables Affect Evolutionary Dynamics

arXiv:2605.15769v1 Announce Type: cross Abstract: The co-optimization of a robot's body and brain presents a coupled challenge: the morphology constrains which control strategies are effective, while

agentsarxiv-cs-ai

LangSmith Engine automates the full agent fix loop — detecting failures, diagnosing causes and drafting PRs. But multi-model enterprises say…

LangSmith Engine automates the full agent fix loop — detecting failures, diagnosing causes and drafting PRs. But multi-model enterprises say a neutral observability layer still wins. http://venturebea

agentsharrison-chase--x

LAPS: Improving Incremental LiDAR Mapping using Active Pooling and Sampling for Neural Distance Fields

arXiv:2605.15496v1 Announce Type: cross Abstract: Neural distance fields offer a compact and continuous representation of 3D geometry, making them attractive for incremental LiDAR mapping. However, th

applicationsarxiv-cs-cv

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

arXiv:2603.25099v2 Announce Type: replace-cross Abstract: We present a framework in which a large language model (LLM) acts as an online adaptive controller for SIMP topology optimization, replacing c

Large Language Models Could Be Rote Learners

arXiv:2504.08300v5 Announce Type: replace-cross Abstract: Benchmark-based evaluation, e.g., multiple-choice questions (MCQs) and open-ended questions (OEQs), is widely used for evaluating Large Langua

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation

arXiv:2512.19701v2 Announce Type: replace-cross Abstract: Accurate prediction of resource consumption and runtime for cloud workflow jobs is critical for scheduling efficiency, yet remains challenging

last week, a friend was telling me how running down a steep trail is great cognitive exercise due to the vast amount of quick processing you…

last week, a friend was telling me how running down a steep trail is great cognitive exercise due to the vast amount of quick processing you do from vision and tactile input to micro adjustments requi

agentsyohei-nakajima--x

Industry

Last year, China added as much energy to its grid as Germany has in total.

In 2023, China's annual energy capacity additions exceeded Germany's total installed energy capacity, highlighting the scale of China's infrastructure expansion and renewable energy deployment. This c

industryelon-musk--x

Latent Video Prediction Learns Better World Models

arXiv:2605.15618v1 Announce Type: cross Abstract: Self-supervised video models are increasingly framed as world models, yet their evaluation remains largely confined to a single top-1 accuracy score o

researcharxiv-cs-ai

LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification

arXiv:2603.10881v2 Announce Type: replace Abstract: Electroencephalogram (EEG) classification plays a key role in medical diagnosis and brain-computer interfaces, but remains challenging due to low si

researcharxiv-cs-lg

Layer Equivalence Is Not a Property of Layers Alone: How You Test Redundancy Changes What You Find

arXiv:2605.16234v1 Announce Type: cross Abstract: When researchers ask whether two transformer layers are 'equivalent' for compression, they often conflate distinct tests. Replacement asks whether one

Layer Selection in Feature-Based Losses Affects Image Quality and Microstructural Consistency in Deep Learning Super-Resolution of Brain Diffusion MRI

arXiv:2605.15895v1 Announce Type: cross Abstract: Clinical application of high-resolution diffusion MRI is hindered by hardware limitations and prohibitive scan times, motivating computational super-r

researcharxiv-cs-cv

Layer-wise Derivative Controlled Networks

arXiv:2605.15463v1 Announce Type: new Abstract: As machine learning models grow in complexity, they increasingly struggle with three conflicting demands: the need for high accuracy, the requirement fo

applicationsarxiv-cs-lg

Tutorials

LDGuid: A Framework for Robust Change Detection via Latent Difference Guidance

arXiv:2605.15582v1 Announce Type: new Abstract: Modern deep learning models for change detection (CD) often struggle to explicitly represent task-relevant semantic differences. This paper proposes the

tutorialsarxiv-cs-cv

LEAP: Trajectory-Level Evaluation of LLMs in Iterative Scientific Design

arXiv:2605.15341v1 Announce Type: cross Abstract: LLMs are increasingly deployed in autonomous laboratories, under the assumption that their domain priors and reasoning over iterative feedback let the

agentsarxiv-cs-ai

Tutorials

Learn more about Composer 2.5: http://cursor.com/blog/composer-2-5

Composer 2.5 is a feature or update from Cursor, an AI-powered code editor, likely introducing improvements to its code generation and editing capabilities. The update probably includes enhancements t

tutorialscursor--x

Learn Where Outcomes Diverge: Efficient VLA RL via Probabilistic Chunk Masking

arXiv:2605.16154v1 Announce Type: new Abstract: Reinforcement learning (RL) allows vision-language-action (VLA) policies to generalize beyond their training distribution by optimizing directly for tas

safetyarxiv-cs-lg

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

model-releasesarxiv-cs-cv

arXiv:2605.15760v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard

Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning

arXiv:2605.15975v1 Announce Type: new Abstract: We tackle the challenge of building embodied AI agents that can reliably solve long-horizon planning problems. Imitation learning from demonstrations ha

safetyarxiv-cs-ai

Learning Context-conditioned Gaussian Overbounds for Convolution-Based Uncertainty Propagation

arXiv:2605.15789v1 Announce Type: new Abstract: Uncertainty quantification is essential in safety-critical settings--from autonomous driving to aviation, finance, and health--where decisions must rely

safetyarxiv-cs-lg

Learning Disentangled Representations for Generalized Multi-view Clustering

model-releasesarxiv-cs-cv

arXiv:2605.15640v1 Announce Type: new Abstract: Multi-View Clustering (MVC) has gained significant attention for its ability to leverage complementary information across diverse views. However, existi

Learning Dynamic Pick-and-Place for a Legged Manipulator

arXiv:2605.15713v1 Announce Type: cross Abstract: Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achiev

applicationsarxiv-cs-ai

Learning Dynamic Structural Specialization for Underwater Salient Object Detection

model-releasesarxiv-cs-cv

arXiv:2605.15535v1 Announce Type: new Abstract: Underwater salient object detection (USOD) has attracted increasing attention for underwater visual scene understanding and vision-guided robotic applic

Learning in Structured Stackelberg Games

arXiv:2504.09006v4 Announce Type: replace-cross Abstract: We initiate the study of structured Stackelberg games, a novel form of strategic interaction between a leader and a follower where contextual

safetyarxiv-cs-lg

Learning Normalized Energy Models for Linear Inverse Problems

arXiv:2605.15487v1 Announce Type: cross Abstract: Generative diffusion models can provide powerful prior probability models for inverse problems in imaging, but existing implementations suffer from tw

researcharxiv-cs-cv

Learning Selective Merge Policies for Deadline-Constrained Coded Caching via Deep Reinforcement Learning

arXiv:2605.15236v1 Announce Type: cross Abstract: With the coded caching, the server can use the information the users have cached to serve multiple users at a time by sending a single coded multi-cas

Learning Sim-Grounded Policies for Bimanual Rope Manipulation from Human Teleoperation Data

arXiv:2605.16043v1 Announce Type: cross Abstract: Deformable Linear Objects (DLOs) such as ropes and cables are widely encountered in both household and industrial applications, yet remain challenging

safetyarxiv-cs-ai

Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision

model-releasesarxiv-cs-ro

arXiv:2604.02812v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have recently demonstrated strong capabilities in mapping multimodal observations to robot behaviors. However, most cu

Local Ai

Learning Where It Matters: Geometric Anchoring for Robust Preference Alignment

arXiv:2602.04909v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) and related methods align large language models from pairwise preferences by regularizing updates against a fix

local-aiarxiv-cs-lg

Learning with Conflicts of Interest

arXiv:2605.15504v1 Announce Type: cross Abstract: Financial, social, and political factors often prevent the interests of the owners of ML systems and services and their users from being perfectly ali

researcharxiv-cs-ai

Linked Multi-Model Data on Russian Domestic and Foreign Policy Speeches

arXiv:2605.15886v1 Announce Type: new Abstract: This paper introduces a dataset of interlinked multimodal political communications from the Russian government, addressing persistent deficiencies in th

safetyarxiv-cs-cl

Tutorials

Literary journals are now publishing, and awarding prizes to, AI written stories. Surprised this made it into Granta!

tutorialsjeremy-howard--x

Literary journals are now publishing, and awarding prizes to, AI written stories. Surprised this made it into Granta! ‘The Serpent in the Grove’ by Jamir Nazir is a story set in rural Trinidad about a

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these change…

model-releasesclem-delangue--x

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these changes is massive and elevates local inference on commodity hardw

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s →…

model-releasesclem-delangue--x

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s → 45 tok/s (+78%). Two flags on llama-server: --spec-type draf

LLM apps fail in ways normal logs can’t explain. Same input, different outputs. Subtle drift. Silent hallucinations. That’s the problem spac…

LLM apps fail in ways normal logs can’t explain. Same input, different outputs. Subtle drift. Silent hallucinations. That’s the problem space LangSmith by @LangChain was built for: observability + eva

agentsharrison-chase--x

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

arXiv:2511.19931v2 Announce Type: replace-cross Abstract: Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various dom

LoCO: Low-rank Compositional Rotation Fine-tuning

arXiv:2605.15916v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as an critical technique for adapting large-scale foundation models across natural language process

Logic of Hypotheses: from Zero to Full Knowledge in Neurosymbolic Integration

arXiv:2509.21663v2 Announce Type: replace-cross Abstract: Neurosymbolic integration (NeSy) blends neural-network learning with symbolic reasoning. The field can be split between methods injecting hand

researcharxiv-cs-ai

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity

arXiv:2605.15242v1 Announce Type: new Abstract: The reliability of Healthcare Information Systems (HIS) is frequently compromised by human-induced data entry errors, which existing statistical anomaly

applicationsarxiv-cs-lg

Long Range Frequency Tuning for QML

arXiv:2602.23409v2 Announce Type: replace-cross Abstract: Angle-encoded variational quantum circuits admit a truncated Fourier series representation of their output, but approximating functions with m

Look Before You Leap: Autonomous Exploration for LLM Agents

arXiv:2605.16143v1 Announce Type: new Abstract: Large language model based agents often fail in unfamiliar environments due to premature exploitation: a tendency to act on prior knowledge before acqui

agentsarxiv-cs-ai

Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification

arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence - reusing the same block repeatedly across layer

lots of good things in 0.6 release of deepagents! great write up by sydney

The post discusses positive features and improvements included in version 0.6 of DeepAgents, with Harrison Chase praising a write-up by Sydney that explains these updates. This likely covers new capab

agentsharrison-chase--x

LPDS: Evaluating LLM Robustness Through Logic-Preserving Difficulty Scaling

arXiv:2605.15393v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed to perform tasks with minimal human oversight, it is crucial that these models operate robustl

researcharxiv-cs-lg

LRCP: Low-Rank Compressibility Guided Visual Token Pruning for Efficient LVLMs

arXiv:2605.15621v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal understanding, but their inference cost grows rapidly with the number of visual tokens, e

safetyarxiv-cs-cv

LUIVITON: Learned Universal Interoperable VIrtual Try-ON

arXiv:2509.05030v2 Announce Type: replace Abstract: To enable large-scale reuse of real-world 3D assets, where garments and characters rarely share skeletons, templates, or dense correspondences, we p

safetyarxiv-cs-cv