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Large Language Models Outperform Humans in Fraud Detection and Resistance to Motivated Investor Pressure

arXiv:2604.20652v1 Announce Type: new Abstract: Large language models trained on human feedback may suppress fraud warnings when investors arrive already persuaded of a fraudulent opportunity. We test

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Safety

Large language models perceive cities through a culturally uneven baseline

DGX agent

arXiv:2604.20048v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to describe, evaluate and interpret places, yet it remains unclear whether they do so from a cultural

safetyarxiv-cs-cl

23 Apr 2026

Last night was the biggest disaster in the history of Tesla. Let me walk you through what actually happened on that earnings call, because t…

model-releasesgary-marcus--x

Last night was the biggest disaster in the history of Tesla. Let me walk you through what actually happened on that earnings call, because the headlines are doing you a disservice: Elon Musk got on th

Last week, we launched Gemini 3.1 TTS, our latest and best text-to-speech model. This new model introduces [awe] audio tags, an intuitive wa…

model-releasesgoogle-ai--x

Last week, we launched Gemini 3.1 TTS, our latest and best text-to-speech model. This new model introduces [awe] audio tags, an intuitive way to guide vocal style, pace, and delivery. Here are some ti

Latent Stochastic Interpolants

model-releasesarxiv-cs-lg

arXiv:2506.02276v2 Announce Type: replace Abstract: Stochastic Interpolants (SI) is a powerful framework for generative modeling, capable of flexibly transforming between two probability distributions

LayerTracer: A Joint Task-Particle and Vulnerable-Layer Analysis framework for Arbitrary Large Language Model Architectures

arXiv:2604.20556v1 Announce Type: cross Abstract: Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba. How

Local Ai

LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning

arXiv:2603.06870v2 Announce Type: replace Abstract: Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided. Evaluating on controlled algor

local-aiarxiv-cs-ai

Hardware

lean in

'Lean In' likely refers to a post by Dylan Patel from SemiAnalysis discussing lean manufacturing, operational efficiency, or business strategy concepts, though the specific content cannot be verified

hardwaredylan-patel--x

Learn2Synth: Learning Optimal Data Synthesis Using Hypergradients for Brain Image Segmentation

arXiv:2411.16719v4 Announce Type: replace Abstract: Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Ra

applicationsarxiv-cs-cv

Learning Multi-Modal Whole-Body Control for Real-World Humanoid Robots

arXiv:2408.07295v4 Announce Type: replace-cross Abstract: A major challenge in humanoid robotics is designing a unified interface for commanding diverse whole-body behaviors, from precise footstep seq

applicationsarxiv-cs-ai

Local Ai

Learning Spatial-Temporal Coherent Correlations for Speech-Preserving Facial Expression Manipulation

arXiv:2604.20226v1 Announce Type: new Abstract: Speech-preserving facial expression manipulation (SPFEM) aims to modify facial emotions while meticulously maintaining the mouth animation associated wi

local-aiarxiv-cs-cv

Learning to count small and clustered objects with application to bacterial colonies

arXiv:2604.20030v1 Announce Type: new Abstract: Automated bacterial colony counting from images is an important technique to obtain data required for the development of vaccines and antibiotics. Howev

safetyarxiv-cs-cv

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization

arXiv:2604.20714v1 Announce Type: new Abstract: Designing and optimizing multi-agent systems (MAS) is a complex, labor-intensive process of 'Agent Engineering.' Existing automatic optimization methods

Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning

arXiv:2604.20109v1 Announce Type: cross Abstract: The quadratic assignment problem (QAP) is a fundamental NP-hard task that poses significant challenges for both traditional heuristics and modern lear

applicationsarxiv-cs-ai

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication

arXiv:2604.19895v1 Announce Type: new Abstract: A well-known limitation of AI systems is presumptuousness: the tendency of AI systems to provide confident answers when information may be lacking. This

Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework

model-releasesarxiv-cs-cl

arXiv:2604.20090v1 Announce Type: new Abstract: Cross-lingual chain-of-thought (XCoT) with self-consistency markedly enhances multilingual reasoning, yet existing methods remain costly due to extensiv

Lever: Inference-Time Policy Reuse under Support Constraints

arXiv:2604.20174v1 Announce Type: new Abstract: Reinforcement learning (RL) policies are typically trained for fixed objectives, making reuse difficult when task requirements change. We study inferenc

safetyarxiv-cs-lg

Lexicographic Minimum-Violation Motion Planning using Signal Temporal Logic

arXiv:2604.20428v1 Announce Type: new Abstract: Motion planning for autonomous vehicles often requires satisfying multiple conditionally conflicting specifications. In situations where not all specifi

agentsarxiv-cs-ro

LEXIS: LatEnt ProXimal Interaction Signatures for 3D HOI from an Image

arXiv:2604.20800v1 Announce Type: new Abstract: Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing

researcharxiv-cs-cv

Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems

arXiv:2604.20745v1 Announce Type: cross Abstract: Federated continual learning (FCL) allows distributed autonomous fleets to adapt collaboratively to evolving terrain types across extended mission lif

agentsarxiv-cs-cv

Lightweight LLM Agent Memory with Small Language Models

arXiv:2604.07798v3 Announce Type: replace Abstract: Although LLM agents can leverage tools for complex tasks, they still need memory to maintain cross-turn consistency and accumulate reusable informat

agentsarxiv-cs-ai

Tools

LiteParse is really neat! It does a great job of extracting text from annoying layouts in PDFs (multiple columns for example) It's only avai…

LiteParse is really neat! It does a great job of extracting text from annoying layouts in PDFs (multiple columns for example) It's only available as a Node.js CLI app, so I vibe-coded up this version

toolssimon-willison--x

LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent

arXiv:2604.17931v2 Announce Type: replace Abstract: Reinforcement Learning (RL) has emerged as a powerful training paradigm for LLM-based agents. However, scaling agentic RL for deep research remains

LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

arXiv:2604.20796v1 Announce Type: new Abstract: We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a nativel

researcharxiv-cs-cv

LLAMADRS: Evaluating Open-Source LLMs on Real Clinical Interviews--To Reason or Not to Reason?

model-releasesarxiv-cs-cl

arXiv:2501.03624v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel on many NLP benchmarks, but their behavior on real-world, semi-structured prediction remains underexplored.

LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals

arXiv:2411.10109v2 Announce Type: replace Abstract: Machine learning can predict human behavior well when substantial structured data and well-defined outcomes are available, but these models are typi

agentsarxiv-cs-ai

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

safetyarxiv-cs-ai

LLM-guided phase diagram construction through high-throughput experimentation

arXiv:2604.20304v1 Announce Type: cross Abstract: Constructing phase diagrams for multicomponent alloys requires extensive experimental measurements and is a time-consuming task. Here we investigate w

LLM-Guided Safety Agent for Edge Robotics with an ISO-Compliant Perception-Compute-Control Architecture

arXiv:2604.20193v1 Announce Type: new Abstract: Ensuring functional safety in human-robot interaction is challenging because AI perception is inherently probabilistic, whereas industrial standards req

safetyarxiv-cs-ro

LLM StructCore: Schema-Guided Reasoning Condensation and Deterministic Compilation

arXiv:2604.20560v1 Announce Type: new Abstract: Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of f

researcharxiv-cs-cl

LLMs Can Get 'Brain Rot': A Pilot Study on Twitter/X

arXiv:2510.13928v2 Announce Type: replace-cross Abstract: We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language mode

safetyarxiv-cs-ai

Tutorials

Local Diffusion Models and Phases of Data Distributions

arXiv:2508.06614v2 Announce Type: replace Abstract: As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance i

tutorialsarxiv-cs-lg

Local Ai

Locate-Then-Examine: Grounded Region Reasoning Improves Detection of AI-Generated Images

arXiv:2510.04225v2 Announce Type: replace-cross Abstract: The rapid growth of AI-generated imagery has blurred the boundary between real and synthetic content, raising practical concerns for digital i

local-aiarxiv-cs-ai

Location-Aware Pretraining for Medical Difference Visual Question Answering

arXiv:2603.04950v2 Announce Type: replace-cross Abstract: Differential medical VQA models compare multiple images to identify clinically meaningful changes and rely on vision encoders to capture fine-

researcharxiv-cs-ai

looks like new Pareto frontiers across everything: - Context: 400K context in Codex and a 1M in API - API Pricing: 5/m input and 30/m outp…

looks like new Pareto frontiers across everything: - Context: 400K context in Codex and a 1M in API - API Pricing: 5/m input and 30/m output tokens. - Codex improved its own inference speed 20% lol -

model-releasesswyx--x

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning

model-releasesarxiv-cs-cl

arXiv:2308.03303v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) is crucial for improving their performance on downstream tasks, but full-parameter fine-tuning (Full-FT) is

LTX just dropped an HDR IC-LoRA beta: EXR output, built for production pipelines

applicationsr-stablediffusion

LTX released an HDR IC-LoRA beta that enables precise control over video generation by transferring structure and motion from reference videos, supporting features like EXR output for professional wor

Lucky High Dynamic Range Smartphone Imaging

arXiv:2604.19976v1 Announce Type: new Abstract: While the human eye can perceive an impressive twenty stops of dynamic range, smartphone camera sensors remain limited to about twelve stops despite dec

researcharxiv-cs-cv

Tutorials

Machine Learning for Two-Stage Graph Sparsification for the Travelling Salesman Problem

arXiv:2604.20236v1 Announce Type: new Abstract: High-performance TSP solvers like LKH search within a sparsified candidate graph rather than over all possible edges. Graph sparsification is non-trivia

tutorialsarxiv-cs-lg

Machine learning moment closure models for the radiative transfer equation IV: enforcing symmetrizable hyperbolicity in two dimensions

arXiv:2604.20143v1 Announce Type: cross Abstract: This is our fourth work in the series on machine learning (ML) moment closure models for the radiative transfer equation (RTE). In the first three pap

researcharxiv-cs-lg

Hardware

Making Sense of the Early Universe

UC Santa Cruz astronomers using GPU-accelerated simulations have discovered rotating disk galaxies resembling the Milky Way appearing far earlier in the universe than expected, breaking records for th

hardwarenvidia-blog

MambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentation

arXiv:2604.20286v1 Announce Type: cross Abstract: Recent segmentation models have demonstrated promising efficiency by aggressively reducing parameter counts and computational complexity. However, the

Manila-based Salmon, a consumer finance app targeting underbanked Filipinos, raised 60M in equity and 40M in debt; it raised 310M to date, 160M in equity (Kate Park/TechCrunch)

Kate Park / TechCrunch: Manila-based Salmon, a consumer finance app targeting underbanked Filipinos, raised 60M in equity and 40M in debt; it raised 310M to date, 160M in equity — The Philippines has

applicationstechmeme

MAPRPose: Mask-Aware Proposal and Amodal Refinement for Multi-Object 6D Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2604.20650v1 Announce Type: new Abstract: 6D object pose estimation in cluttered scenes remains challenging due to severe occlusion and sensor noise. We propose MAPRPose, a two-stage framework t

Markov reads Pushkin, again: A statistical journey into the poetic world of Evgenij Onegin

arXiv:2604.20221v1 Announce Type: new Abstract: This study applies symbolic time series analysis and Markov modeling to explore the phonological structure of Evgenij Onegin-as captured through a graph

researcharxiv-cs-cl

MasconCube: Fast and Accurate Gravity Modeling with an Explicit Representation

arXiv:2509.08607v3 Announce Type: replace-cross Abstract: The geodesy of irregularly shaped small bodies presents fundamental challenges for gravitational field modeling, particularly as deep space ex

researcharxiv-cs-lg

MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy

arXiv:2511.11931v2 Announce Type: replace Abstract: This paper proposes MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy, a control policy for active multi-target tracking using a mobi

safetyarxiv-cs-ro

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning

arXiv:2604.20074v1 Announce Type: new Abstract: A popular approach to apprenticeship learning (AL) is to formulate it as an inverse reinforcement learning (IRL) problem. The MaxEnt-IRL algorithm succe

researcharxiv-cs-lg