All entries

Just Pass Twice: Efficient Token Classification with LLMs for Zero-Shot NER

arXiv:2604.05158v2 Announce Type: replace Abstract: Large language models encode extensive world knowledge valuable for zero-shot named entity recognition. However, their causal attention mechanism, w

researcharxiv-cs-cl

Keep It CALM: Toward Calibration-Free Kilometer-Level SLAM with Visual Geometry Foundation Models via an Assistant Eye

DGX agent

arXiv:2604.14795v1 Announce Type: new Abstract: Visual Geometry Foundation Models (VGFMs) demonstrate remarkable zero-shot capabilities in local reconstruction. However, deploying them for kilometer-l

local-aiarxiv-cs-ro

17 Apr 2026

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning

arXiv:2407.00809v3 Announce Type: replace Abstract: This paper introduces the Kernel Neural Operator (KNO), a provably convergent operator-learning architecture that utilizes compositions of deep kern

Industry

Kevin Weil, OpenAI's former CPO who became VP of OpenAI for Science, is leaving the company; Prism, a web app for scientists launched in Jan., will be shuttered (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: Kevin Weil, OpenAI's former CPO who became VP of OpenAI for Science, is leaving the company; Prism, a web app for scientists launched in Jan., will be shuttered — The former Inst

industrytechmeme

Knowing When Not to Answer: Evaluating Abstention in Multimodal Reasoning Systems

arXiv:2604.14799v1 Announce Type: new Abstract: Effective abstention (EA), recognizing evidence insufficiency and refraining from answering, is critical for reliable multimodal systems. Yet existing e

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality

arXiv:2506.19807v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an in

tutorialsarxiv-cs-cl

KVNN: Learnable Multi-Kernel Volterra Neural Networks

arXiv:2604.15141v1 Announce Type: new Abstract: Higher-order learning is fundamentally rooted in exploiting compositional features. It clearly hinges on enriching the representation by more elaborate

researcharxiv-cs-cv

Label-efficient underwater species classification with logistic regression on frozen foundation model embeddings

model-releasesarxiv-cs-cv

arXiv:2604.00313v2 Announce Type: replace Abstract: Automated species classification from underwater imagery is bottlenecked by the cost of expert annotation, and supervised models trained on one data

Language Model as Planner and Formalizer under Constraints

arXiv:2510.05486v2 Announce Type: replace Abstract: LLMs have been widely used in planning, either as planners to generate action sequences end-to-end, or as formalizers to represent the planning doma

Applications

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions

arXiv:2502.16761v2 Announce Type: replace Abstract: Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stage

applicationsarxiv-cs-cl

Language of Thought Shapes Output Diversity in Large Language Models

arXiv:2601.11227v2 Announce Type: replace Abstract: Output diversity is crucial for Large Language Models as it underpins pluralism and creativity. In this work, we reveal that controlling the languag

Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality

arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode

Applications

Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends

arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as

applicationsarxiv-cs-ai

Local Ai

Large Vision Model-Guided Masked Low-Rank Approximation for Ground-Roll Attenuation

arXiv:2604.00998v2 Announce Type: replace Abstract: Ground roll is a common type of coherent noise in seismic records, and its attenuation remains challenging due to its substantial overlap with usefu

local-aiarxiv-cs-cv

Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabi…

model-releasesemad-mostaque--x

Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabilities they couldn't release it. The announcement featured A

Latent Wavelet Diffusion For Ultra-High-Resolution Image Synthesis

arXiv:2506.00433v4 Announce Type: replace Abstract: High-resolution image synthesis remains a core challenge in generative modeling, particularly in balancing computational efficiency with the preserv

researcharxiv-cs-cv

Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents

arXiv:2604.14717v1 Announce Type: cross Abstract: Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior

safetyarxiv-cs-lg

Hardware

LayerScope: Predictive Cross-Layer Scheduling for Efficient Multi-Batch MoE Inference on Legacy Servers

arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor

hardwarearxiv-cs-lg

Lazy or Efficient? Towards Accessible Eye-Tracking Event Detection Using LLMs

arXiv:2604.13243v1 Announce Type: cross Abstract: Gaze event detection is fundamental to vision science, human-computer interaction, and applied analytics. However, current workflows often require spe

researcharxiv-cs-ai

LeapAlign: Post-Training Flow Matching Models at Any Generation Step by Building Two-Step Trajectories

arXiv:2604.15311v1 Announce Type: new Abstract: This paper focuses on the alignment of flow matching models with human preferences. A promising way is fine-tuning by directly backpropagating reward gr

safetyarxiv-cs-cv

Learning Ad Hoc Network Dynamics via Graph-Structured World Models

arXiv:2604.14811v1 Announce Type: new Abstract: Ad hoc wireless networks exhibit complex, innate and coupled dynamics: node mobility, energy depletion and topology change that are difficult to model a

safetyarxiv-cs-lg

Learning Adaptive Reasoning Paths for Efficient Visual Reasoning

arXiv:2604.14568v1 Announce Type: cross Abstract: Visual reasoning models (VRMs) have recently shown strong cross-modal reasoning capabilities by integrating visual perception with language reasoning.

Learning and Generating Mixed States Prepared by Shallow Channel Circuits

arXiv:2604.01197v2 Announce Type: replace-cross Abstract: Learning quantum states from measurement data is a central problem in quantum information and computational complexity. In this work, we study

Learning temporal embeddings from electronic health records of chronic kidney disease patients

arXiv:2601.18675v2 Announce Type: replace Abstract: We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations w

tutorialsarxiv-cs-lg

Learning to Concatenate Quantum Codes

arXiv:2604.14931v1 Announce Type: cross Abstract: Concatenating quantum error correction codes scales error correction capability by driving logical error rates down double-exponentially across levels

Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making

arXiv:2512.17091v2 Announce Type: replace Abstract: We propose a new approach for solving planning problems with a hierarchical structure, fusing reinforcement learning and MPC planning. Our formulati

tutorialsarxiv-cs-lg

Learning to Think Like a Cartoon Captionist: Incongruity-Resolution Supervision for Multimodal Humor Understanding

arXiv:2604.15210v1 Announce Type: cross Abstract: Humor is one of the few cognitive tasks where getting the reasoning right matters as much as getting the answer right. While recent work evaluates hum

Learning Where to Embed: Noise-Aware Positional Embedding for Query Retrieval in Small-Object Detection

model-releasesarxiv-cs-cv

arXiv:2604.15065v1 Announce Type: new Abstract: Transformer-based detectors have advanced small-object detection, but they often remain inefficient and vulnerable to background-induced query noise, wh

Let's talk content faithfulness. Four days ago, we launched ParseBench, the first document OCR benchmark for AI agents. Its most fundamental…

model-releasesjerry-liu--x

Let's talk content faithfulness. Four days ago, we launched ParseBench, the first document OCR benchmark for AI agents. Its most fundamental metric asks: did the parser capture all the text, in order,

Leveraging graph neural networks and mobility data for COVID-19 forecasting

arXiv:2501.11711v2 Announce Type: replace Abstract: The COVID-19 pandemic has claimed millions of lives, spurring the development of diverse forecasting models. In this context, the true utility of co

LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence

arXiv:2512.04578v3 Announce Type: replace Abstract: Legal general intelligence (GI) refers to artificial intelligence (AI) that encompasses legal understanding, reasoning, and decision-making, simulat

Listen, Correct, and Feed Back: Spoken Pedagogical Feedback Generation

arXiv:2604.14177v1 Announce Type: new Abstract: Grammatical error correction (GEC) and explanation (GEE) have made rapid progress, but real teaching scenarios also require learner-friendly pedagogical

Listen to the OpenAI Podcast on— Spotify https://open.spotify.com/show/0zojMEDizKMh3aTxnGLENP Apple https://podcasts.apple.com/us/podcast/op…

Listen to the OpenAI Podcast on— Spotify https://open.spotify.com/show/0zojMEDizKMh3aTxnGLENP Apple https://podcasts.apple.com/us/podcast/openai-podcast/id1820330260 YouTube https://youtu.be/UZyH0nx5z

model-releasesopenai--x

Listening Alone, Understanding Together: Collaborative Context Recovery for Privacy-Aware AI

arXiv:2604.13348v1 Announce Type: new Abstract: We introduce CONCORD, a privacy-aware asynchronous assistant-to-assistant (A2A) framework that leverages collaboration between proactive speech-based AI

researcharxiv-cs-ai

LLM agents loop, drift, and get stuck on hard reasoning tasks up to 30% of the time. Current fixes are either too blunt (hard step limits) o…

LLM agents loop, drift, and get stuck on hard reasoning tasks up to 30% of the time. Current fixes are either too blunt (hard step limits) or too expensive (LLM-as-judge adding 10-15% overhead per ste

tutorialsdair-ai--x

LLM Predictive Scoring and Validation: Inferring Experience Ratings from Unstructured Text

arXiv:2604.14321v1 Announce Type: new Abstract: We tasked GPT-4.1 to read what baseball fans wrote about their game-day experience and predict the overall experience rating each fan gave on a 0-10 sur

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems

model-releasesarxiv-cs-cv

arXiv:2601.14053v2 Announce Type: replace-cross Abstract: The field of artificial intelligence has undergone a revolution from foundational Transformer architectures to reasoning-capable systems appro

LLMs Gaming Verifiers: RLVR can Lead to Reward Hacking

model-releasesarxiv-cs-lg

arXiv:2604.15149v1 Announce Type: new Abstract: As reinforcement Learning with Verifiable Rewards (RLVR) has become the dominant paradigm for scaling reasoning capabilities in LLMs, a new failure mode

Agents

LM Studio 0.4.12 is out now - @Alibaba_Qwen Qwen3.6 support! - Nicer PDF exports for chats - MCP servers with OAuth work on Windows - Better…

LM Studio version 0.4.12 introduces support for Alibaba's Qwen 3.6 model, improved PDF export functionality for chat conversations, and fixes for MCP (Model Context Protocol) servers with OAuth authen

agentslm-studio--x

Local Ai

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting

arXiv:2505.11017v2 Announce Type: replace Abstract: Time series forecasting is critical across multiple domains, where time series data exhibit both local patterns and global dependencies. While Trans

local-aiarxiv-cs-lg

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning

arXiv:2604.14922v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has emerged as a critical driver for enhancing the reasoning capabilities of Large Language Models (LLMs). While recent ad

Industry

Looking for some beta testers for our new robotics dataset hosting features. Who's currently hosting large robotics datasets and would be do…

Clem Delangue, CEO of Hugging Face, is soliciting beta testers for new dataset hosting features specifically designed for robotics data. The post seeks to identify organizations and researchers curren

industryclem-delangue--x

@_lopopolo @aiDotEngineer @badlogicgames Harnes Engineering talk: https://x.com/aiDotEngineer/status/2044937501593460773?s=20

@_lopopolo @aiDotEngineer @badlogicgames Harnes Engineering talk: https://x.com/aiDotEngineer/status/2044937501593460773?s=20 🆕 Harness Engineering: How to Build Software When Humans Steer, Agents Exe

tutorialsswyx--x

Tools

@_lopopolo @aiDotEngineer @badlogicgames Slow Down talk: https://x.com/aiDotEngineer/status/2044915752072036420?s=20

@_lopopolo @aiDotEngineer @badlogicgames Slow Down talk: https://x.com/aiDotEngineer/status/2044915752072036420?s=20 🆕 Building pi in a World of Slop https://www.youtube.com/watch?v=RjfbvDXpFls @badlo

toolsswyx--x

Industry

Lot of catching up to do. xAI is half the age or less of competitors.

xAI, Elon Musk's artificial intelligence company, is significantly younger than established competitors in the AI industry, requiring substantial development to catch up. The statement acknowledges th

industryelon-musk--x

Low-Cost System for Automatic Recognition of Driving Pattern in Assessing Interurban Mobility using Geo-Information

arXiv:2604.15216v1 Announce Type: cross Abstract: Mobility in urban and interurban areas, mainly by cars, is a day-to-day activity of many people. However, some of its main drawbacks are traffic jams

M3D-Net: Multi-Modal 3D Facial Feature Reconstruction Network for Deepfake Detection

arXiv:2604.14574v1 Announce Type: new Abstract: With the rapid advancement of deep learning in image generation, facial forgery techniques have achieved unprecedented realism, posing serious threats t

researcharxiv-cs-cv

MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events

arXiv:2604.15203v1 Announce Type: new Abstract: Machine learning in high-stakes domains such as healthcare requires not only strong predictive performance but also reliable uncertainty quantification