All entries

Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions

model-releasesarxiv-cs-lg

arXiv:2605.19562v1 Announce Type: cross Abstract: This paper presents a learning-augmented trajectory planning framework for cooperative unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV)

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Learning Efficient Guardrails for Compliance

DGX agent

arXiv:2510.03485v2 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed for long-horizon tasks, yet their ability to adhere to real-world policies remains critically undere

model-releasesarxiv-cs-ai

20 May 2026

Tutorials

Learning Interpretable Point-Based Clinical Risk Scores via Direct Optimization

arXiv:2605.19113v1 Announce Type: cross Abstract: Many clinical risk scores are deployed as additive rules with nonnegative integer points assigned to relevant binary predictive features. These intege

tutorialsarxiv-cs-lg

Learning Long-Term Temporal Dependencies in Photovoltaic Power Output Prediction Through Multi-Horizon Forecasting

arXiv:2605.19074v1 Announce Type: cross Abstract: The rapid global expansion of solar photovoltaic (PV) capacity-reaching a record 597 GW in 2024-highlights the urgent need for robust forecasting mode

Learning ORDER-Aware Multimodal Representations for Composite Materials Design

arXiv:2602.02513v2 Announce Type: replace Abstract: Artificial intelligence has shown remarkable success in materials discovery and property prediction, particularly for crystalline and polymer system

safetyarxiv-cs-lg

Learning Orthonormal Bases for Function Spaces

arXiv:2605.19959v1 Announce Type: new Abstract: Infinite-dimensional orthonormal basis expansions play a central role in representing and computing with function spaces due to their favorable linear a

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

arXiv:2602.04998v2 Announce Type: replace-cross Abstract: Low-Rank Adaptation (LoRA) is the prevailing approach for efficient large language model (LLM) fine-tuning. Building on this paradigm, recent

Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

arXiv:2605.19140v1 Announce Type: new Abstract: We study workflow learning in a setting where specialized agents hand off control through a shared artifact, each agent observes only a local function o

local-aiarxiv-cs-ai

Learning When to Adapt

model-releasesarxiv-cs-lg

arXiv:2605.19028v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) is a widely used parameter-efficient fine-tuning method, yet its learned correction is static: the same low-rank update is ap

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction

arXiv:2605.19975v1 Announce Type: cross Abstract: Neural policies have shown promise in solving vehicle routing problems due to their reduced reliance on handcrafted heuristics. However, current train

safetyarxiv-cs-ai

Industry

Leaving the V8 in the past: The all-electric Mercedes-AMG GT 4-Door

Mercedes-AMG has unveiled the all-electric GT 4-Door, the first all-electric model in AMG history , powered by three axial flux motors with a 106-kWh battery and featuring a rear-biased all-wheel-driv

industryars-technica

Lens Privacy Sealing: A New Benchmark and Method for Physical Privacy-Preserving Action Recognition

arXiv:2605.19578v1 Announce Type: cross Abstract: RGB camera-based surveillance systems enable human action recognition for public safety and healthcare, yet raise serious privacy concerns. Existing m

Less Back-and-Forth: A Comparative Study of Structured Prompting

arXiv:2605.20149v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used for open-ended tasks, but underspecified prompts can lead to low-quality answers and additional interacti

Less is More: Efficient Black-box Attribution via Minimal Interpretable Subset Selection

arXiv:2504.00470v2 Announce Type: replace-cross Abstract: To develop a trustworthy AI system, which aim to identify the input regions that most influence the models decisions. The primary task of exis

researcharxiv-cs-cv

Tools

Less noise = more signal. Vital content per snippet is up 63%. Ads, navigation, metadata, and unhelpful content are culled before handoff to…

Less noise = more signal. Vital content per snippet is up 63%. Ads, navigation, metadata, and unhelpful content are culled before handoff to the answer model. On SimpleQA, we achieve a 50x compression

toolsperplexity--x

Agents

Library Drift: Diagnosing and Fixing a Silent Failure Mode in Self-Evolving LLM Skill Libraries

arXiv:2605.19576v1 Announce Type: new Abstract: Self-evolving skill libraries face a silent failure mode we term library drift: unbounded skill accumulation without outcome-driven lifecycle management

agentsarxiv-cs-ai

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries

model-releasesarxiv-cs-cl

arXiv:2509.22202v3 Announce Type: replace-cross Abstract: Large language models (LLMs) now play a central role in code generation, yet they continue to hallucinate, frequently inventing non-existent l

LIFT and PLACE: A Simple, Stable, and Effective Knowledge Distillation Framework for Lightweight Diffusion Models

arXiv:2605.19729v1 Announce Type: cross Abstract: We demonstrate that in knowledge distillation for diffusion models, the teacher network's highly complex denoising process - stemming from its substan

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators

arXiv:2605.19060v1 Announce Type: cross Abstract: High-resolution 3D medical image generation remains challenging because fully volumetric models are computationally expensive, while efficient 2D slic

Lightweight and Fast Backdoor Model Detection

arXiv:2605.18907v1 Announce Type: cross Abstract: Deep neural networks (DNN), despite their remarkable performance, are highly vulnerable to backdoor attacks. Existing defenses mainly rely on activati

LionMuon: Alternating Spectral and Sign Descent for Efficient Training

arXiv:2605.19811v1 Announce Type: new Abstract: In large-scale optimization, the cheapness and effectiveness of update steps are the most crucial factors for a successful optimizer. Sign-based optimiz

Industry

Lithuania becomes second European country to approve FSD Supervised

Lithuania has approved Tesla's Full Self-Driving (FSD) Supervised feature, becoming the second European country to do so after another nation's prior approval. This regulatory clearance allows Tesla t

industryelon-musk--x

LLM agents & memory systems operate in continuously updated environments (Git repos, evolving docs). They must process long contexts, recove…

LLM agents & memory systems operate in continuously updated environments (Git repos, evolving docs). They must process long contexts, recover earlier information, and reason over many updates that cre

safetyjeremy-howard--x

LLM-Based Financial Sentiment Analysis in Arabic: Evidence from Saudi Markets

arXiv:2605.19714v1 Announce Type: new Abstract: Investor sentiment shapes financial markets, yet modeling sentiment in Arabic financial contexts remains challenging due to linguistic complexity and li

researcharxiv-cs-cl

LLM Benchmark Datasets Should Be Contamination-Resistant

arXiv:2605.19999v1 Announce Type: cross Abstract: Benchmark datasets are critical for reproducible, reliable, and discriminative evaluation of LLMs. However, recent studies reveal that many benchmark

Applications

LLM-MC-Affect: LLM-Based Monte Carlo Modeling of Affective Trajectories and Latent Ambiguity for Interpersonal Dynamic Insight

arXiv:2601.03645v2 Announce Type: replace Abstract: Emotional coordination is a core property of human interaction that shapes how relational meaning is constructed in real time. While text-based affe

applicationsarxiv-cs-cl

LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening

model-releasesarxiv-cs-cl

arXiv:2605.19597v1 Announce Type: new Abstract: Evaluating large language models (LLMs) on natural-language logical reasoning is essential because rule-governed tasks require conclusions to follow str

Agents

LLMs are stateless (every time you reply to an LLM, you re-inject the entire conversation to a fresh inference) the purpose of memory is to …

LLMs are stateless (every time you reply to an LLM, you re-inject the entire conversation to a fresh inference) the purpose of memory is to provide continuity (in games we'd call it a 'persistent worl

agentsyohei-nakajima--x

LMM-Track4D: Eliciting 4D Dynamic Reasoning in LMMs via Trajectory-Grounded Dialogue

model-releasesarxiv-cs-cv

arXiv:2605.19390v1 Announce Type: new Abstract: Recent large multimodal models (LMMs) have become increasingly capable on image and video understanding, yet still struggle to sustain 4D continuous spa

Local LLM - privacy first - doctor

A discussion from the r/ollama community about using local large language models for privacy-sensitive applications, particularly for handling sensitive documents like medical records. Local LLMs proc

local-air-ollama

Locate-then-Sparsify: Attribution Guided Sparse Strategy for Visual Hallucination Mitigation

arXiv:2603.16284v2 Announce Type: replace Abstract: Despite the significant advancements in Large Vision-Language Models (LVLMs), their tendency to generate hallucinations undermines reliability and r

researcharxiv-cs-cv

Industry

London-based Primer, which helps e-commerce merchants connect and manage multiple payment providers, raised a $100M Series C led by Sofina (Damisola Sulaiman/Sifted)

Damisola Sulaiman / Sifted: London-based Primer, which helps e-commerce merchants connect and manage multiple payment providers, raised a 100M Series C led by Sofina — The London-based fintech is doub

industrytechmeme

Applications

Long-term Power Grid Planning via Answer Set Programming

arXiv:2605.20172v1 Announce Type: cross Abstract: The Power grid is a critical infrastructure underpinning all aspects of modern society and its services. Maintaining its effectiveness requires contin

applicationsarxiv-cs-ai

LoRA vs. Full Fine-Tuning: A Theoretical Perspective

arXiv:2605.19018v1 Announce Type: new Abstract: Fine-tuning adapts a pre-trained model to downstream tasks using a small amount of labeled data. Low-Rank Adaptation (LoRA) is an efficient fine-tuning

Lossless Anti-Distillation Sampling

arXiv:2605.18829v1 Announce Type: new Abstract: Frontier commercial generative models face a growing threat from distillation, whereby a distiller harvests generated responses and trains a competing m

Lost and Found in Translation: Variational Diagnostics for Neural Codebook Channels

arXiv:2605.18846v1 Announce Type: cross Abstract: Classical communication systems fail not only through random noise but also when transmitter and receiver use incompatible operational codebooks. Vari

Lost in Interpretation: The Plausibility-Faithfulness Trade-off in Cross-Lingual Explanations

arXiv:2605.19274v1 Announce Type: new Abstract: LLMs deployed multilingually are often audited via English explanations for non-English inputs. We evaluate extractive explanations ''where the model id

researcharxiv-cs-cl

Agents

Love this concept. Always been a proponent of event-driven architectures, and the actor model. Neat to see how it’s applied to the agent run…

Love this concept. Always been a proponent of event-driven architectures, and the actor model. Neat to see how it’s applied to the agent runtime here. i'm excited to open source Active Graph: an event

agentsyohei-nakajima--x

Low-Compute Watermark Removal via Dual-Domain Natural Projection

arXiv:2510.07538v2 Announce Type: replace Abstract: Effective removal of semantic watermarks requires balancing three competing objectives: high removal success, low perceptual distortion, and low com

safetyarxiv-cs-cv

Applications

LP-Eval: Rubric and Dataset for Measuring the Quality of Legal Proposition Generation

arXiv:2605.19815v1 Announce Type: cross Abstract: Legal proposition generation is central to legal reasoning and doctrinal scholarship, yet remain under-examined in Legal NLP. This paper investigates

applicationsarxiv-cs-ai

📽️ LTX 2.3 IC LoRAs - LipDub & Video Utilities 🎤 Hosts: Purz & Rob ⏲️ May 20th – 3pm PST / 6pm EST 📍 Live on YouTube, X, and Twitch Today…

📽️ LTX 2.3 IC LoRAs - LipDub & Video Utilities 🎤 Hosts: Purz & Rob ⏲️ May 20th – 3pm PST / 6pm EST 📍 Live on YouTube, X, and Twitch Today we're diving into LTX 2.3 IC LoRAs to check out LipDub and a b

local-aicomfyui--x

LTX 2.3 IC LoRAs (LipDub and Video Utilities) https://x.com/i/broadcasts/1qKDzPZeLjVJV

LTX 2.3 IC introduces specialized LoRA (Low-Rank Adaptation) modules for video generation, including LipDub functionality for synchronized lip movements and Video Utilities for enhanced video processi

local-aicomfyui--x

LTX Color Shifting

local-air-stablediffusion

The post discusses a color shifting issue observed when using LTX model in Stable Diffusion, where generated images exhibit unwanted color variations or drift during processing. Community members like

LWiAI Podcast #245 - TML-Interaction, Claude For Legal, Sam Altman on Stand

model-releaseslast-week-in-ai

This podcast episode covers three main topics: TML-Interaction (likely a new AI model or technical development), the application of Claude AI in legal settings and use cases, and Sam Altman's testimon

Lying Is Just a Phase: The Hidden Alignment Transition in Language Model Scaling

arXiv:2605.18838v1 Announce Type: cross Abstract: Scaling laws predict loss from compute but not how capabilities interact. We measure the coupling between reasoning and truthfulness across 63 base mo

Lynx: Enabling Efficient MoE Inference through Dynamic Batch-Aware Expert Selection

model-releasesarxiv-cs-lg

arXiv:2411.08982v3 Announce Type: replace Abstract: Selective parameter activation provided by Mixture-of-Expert (MoE) models have made them a popular choice in modern foundational models. However, Mo

m3BERT: A Modern, Multi-lingual, Matryoshka Bidirectional Encoder

model-releasesarxiv-cs-cl

arXiv:2605.19568v1 Announce Type: new Abstract: Embedding models are pivotal in industrial information retrieval systems like search and advertising. However, existing pretrained models often exhibit

M3DocDep: Multi-modal, Multi-page, Multi-document Dependency Chunking with Large Vision-Language Models

arXiv:2605.18774v1 Announce Type: cross Abstract: In long, multi-page industrial documents, retrieval-augmented generation (RAG) depends heavily on whether chunk boundaries follow the document's true