Search: “models”

Exploring Agentic Tool-Calling Decisions via Uncertainty-Aligned Reinforcement Learning

arXiv:2606.06976v1 Announce Type: new Abstract: Large language model (LLM)-based agents often make suboptimal tool-use decisions, including unsupported tool invocation and hallucinated direct response

agentsarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability

DGX agent

arXiv:2606.07150v1 Announce Type: cross Abstract: Agent-interoperability protocols such as A2A and MCP standardize what agents say to one another, but assume address-based transport over HTTP(S). Such

agentsarxiv-cs-ai

8 Jun 2026

FrontierCode has three task sets: Extended (150 tasks), Main (100 tasks) and Diamond (50 tasks). SOTA LLMs have significant room for improve…

FrontierCode has three task sets: Extended (150 tasks), Main (100 tasks) and Diamond (50 tasks). SOTA LLMs have significant room for improvement, with the top model earning a score of just 13.4/100 on

agentscognition-ai--x

@GaryMarcus Marcus isn't wrong. Everyone bolts tools onto transformers because they hit walls fast. Neurosymbolic AI is rising for a reason:…

Gary Marcus argues that large language models based on transformers quickly reach their limitations, prompting developers to add external tools as workarounds, while neurosymbolic AI—which combines ne

safetygary-marcus--x

Gaussian Process Latent Factor Regression for Low-Data, High-Dimensional Output Problems

arXiv:2606.06576v1 Announce Type: new Abstract: In the sciences, regression tasks often require predicting high-dimensional outputs from few training examples. Multi-output Gaussian processes excel in

GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection

arXiv:2606.07102v1 Announce Type: cross Abstract: We propose GP-Adapter, a training-free framework that augments CLIP (Contrastive Language-Image Pre-training) with Gaussian Process (GP) uncertainty m

Industry

Great paper from @JonSaadFalcon @Avanika15 @HazyResearch: https://huggingface.co/papers/2511.07885

This paper from researchers at Hazy Research (Jon Saad-Falcon and Avanika Narayan) appears to present novel research findings, likely related to machine learning, language models, or AI systems given

industryclem-delangue--x

Tutorials

Hard labels sampled from sparse targets mislead rotation invariant algorithms

arXiv:2603.20967v2 Announce Type: replace-cross Abstract: One of the most common machine learning setups is logistic regression. In many classification models, including neural networks, the final pre

tutorialsarxiv-cs-lg

Impact of Synthetic Lesional MR Images in Automated Focal Cortical Dysplasia Detection in Low-Data Scenarios

arXiv:2606.07381v1 Announce Type: cross Abstract: Background and Purpose: Automated detection of focal cortical dysplasia (FCD) requires large volumes of voxelwise lesion-delineated MRI data, which ar

Introducing FrontierCode: a coding eval that raises the bar for difficulty & quality. Each task took 40+ hrs of work by leading open-source …

Introducing FrontierCode: a coding eval that raises the bar for difficulty & quality. Each task took 40+ hrs of work by leading open-source maintainers. Models write sloppy code that works but isn’t m

agentscognition-ai--x

Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates

arXiv:2601.18510v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents excel at general tasks, they inherently struggle with continual adaptation due to the frozen weights a

Limitations of Normalization in Attention Mechanism

arXiv:2508.17821v3 Announce Type: replace-cross Abstract: This paper investigates the limitations of the normalization in attention mechanisms. We begin with a theoretical framework that enables the i

Mining Useful General Data for Low-Resource Domain Adaptation

arXiv:2511.07380v2 Announce Type: replace Abstract: Adapting large language models (LLMs) to low-resource domains remains challenging due to the scarcity of domain-specific data. While in-domain data

safetyarxiv-cs-cl

Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA

arXiv:2603.24481v2 Announce Type: replace Abstract: Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings. A model that is always overconfident offers no useful

agentsarxiv-cs-ai

Planning-aligned Token Compression for Long-Context Autonomous Driving

arXiv:2606.07464v1 Announce Type: cross Abstract: Monolithic vision-action models represent an emerging paradigm in autonomous driving. However, this architecture produces token sequences that quickly

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards

arXiv:2606.06825v1 Announce Type: cross Abstract: Reinforcement learning has recently shown promise in improving large language models for Text-to-SQL generation, yet existing methods typically optimi

Applications

Proxy Reconstruction Pre-training for Ramp Flow Prediction at Highway Interchanges

arXiv:2510.03381v3 Announce Type: replace-cross Abstract: Interchanges are crucial nodes for vehicle transfers between highways, yet the lack of real-time ramp detectors creates blind spots in traffic

applicationsarxiv-cs-ai

RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs

arXiv:2604.17948v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across various cybersecurity tasks, including vulnerability classificat

SCALE: Scalable Cross-Attention Learning with Extrapolation for Agentic Workflow Scheduling

arXiv:2606.06820v1 Announce Type: cross Abstract: Agentic Large Language Model (LLM) systems decompose complex tasks into workflow Directed Acyclic Graphs (DAGs) whose primitives must be scheduled on

agentsarxiv-cs-ai

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation

arXiv:2602.19213v2 Announce Type: replace Abstract: Medical image segmentation is vital for clinical diagnosis and quantitative analysis, yet remains challenging due to the heterogeneity of imaging mo

researcharxiv-cs-cv

Self-evolving LLM agents with in-distribution Optimization

arXiv:2606.07367v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently emerged as powerful controllers for interactive agents in complex environments, yet training them to perform

safetyarxiv-cs-lg

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs

arXiv:2606.06574v1 Announce Type: new Abstract: Large language models (LLMs) perform inference by following a fixed depth and order, non-recurrent execution of all layers. We reveal the wide existence

SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal

arXiv:2606.07351v1 Announce Type: cross Abstract: Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EE

Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills

arXiv:2606.07412v1 Announce Type: cross Abstract: LLM-driven software engineering agents have become a central testbed for real-world language-model capability, yet their training remains limited by t

Industry

Thanks again for your interest in our work! Links here so they don’t get buried under “show more”: Paper 📄: https://arxiv.org/abs/2606.0237…

Thanks again for your interest in our work! Links here so they don’t get buried under “show more”: Paper 📄: https://arxiv.org/abs/2606.02373 Code 💻: https://github.com/pat-jj/harness-1 Model 🤗: https:

industryclem-delangue--x

The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces

arXiv:2606.06814v1 Announce Type: cross Abstract: The transformer's emergent ability to perform in-context learning (ICL) has sparked a wide range of studies designed to understand its underlying mech

The Utility and Complexity of in- and out-of-Distribution Machine Unlearning

arXiv:2412.09119v3 Announce Type: replace Abstract: Machine unlearning, the process of selectively removing data from trained models, is increasingly crucial for addressing privacy concerns and knowle

Translate-R1: Cost-Aware Translation Tool Use via Reinforcement Learning

arXiv:2606.06835v1 Announce Type: new Abstract: The performance gap across languages in LLMs is well documented, and closing it natively requires pretraining or fine-tuning on corpora that, for most l

safetyarxiv-cs-cl

When CLIP Sees More, It Fights Back Harder: Multi-View Guided Adaptive Counterattacks for Test-Time Adversarial Robustness

arXiv:2606.06938v1 Announce Type: new Abstract: Vision-language models such as CLIP have achieved remarkable zero-shot recognition capabilities, yet their robustness against adversarial perturbations

researcharxiv-cs-cv

Whisper Hallucination Detection and Mitigation via Hidden Representation Steering and Sparse AutoEncoders

arXiv:2606.07473v1 Announce Type: cross Abstract: Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconne

Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition

arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper

blast from the past 3.5 years ago; some things have changed (esp. coding and math, via neurosymbolic techniques) but many haven’t:

blast from the past 3.5 years ago; some things have changed (esp. coding and math, via neurosymbolic techniques) but many haven’t: Bottom line: From the outset Large Language Models like GPT-3 have gr

safetygary-marcus--x

Local Ai

Bro just keeps cooking! 🔥

ComfyUI, a node-based UI framework for Stable Diffusion and other AI models, continues active development and feature releases. The post celebrates ongoing progress and improvements to the platform, l

local-aicomfyui--x

Industry

Image Gen limit?

ChatGPT Plus users can generate approximately 50 images per rolling 3-hour window , with a daily maximum of around 200 images . Recent product updates have introduced new image models and occasional t

industryr-chatgpt

Syntheses

Wiki Lint Report — 2026-06-07

linthealth-checkautomated

Automated lint: 47 errors, 12 warnings, 3 info

An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)

arXiv:2606.05357v1 Announce Type: new Abstract: Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction wit

Benchmarks in Leipzig

arXiv:2606.05818v1 Announce Type: cross Abstract: Between April 1 and May 15, 2026, a group of 49 mathematicians compiled a dataset of research-level mathematics questions with known answers. Most of

Applications

Binary Gaussian Copula Synthesis: an LLM-powered data augmentation framework for early dialysis prediction in chronic kidney disease

arXiv:2403.00965v2 Announce Type: replace-cross Abstract: Only a small fraction of patients with chronic kidney disease (CKD) progress to dialysis, creating severe class imbalance that limits the perf

applicationsarxiv-cs-ai

Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentation

arXiv:2606.06345v1 Announce Type: new Abstract: Brain decoding is limited by the availability of labeled neural data, and remains challenging in low-data regimes. To address this issue, we investigate

Conformal Risk-Averse Decision Making with Action Conditional Guarantee

arXiv:2606.05551v1 Announce Type: cross Abstract: Reliable decision making pipelines powered by machine learning models require uncertainty quantification (UQ) methods that come with explicit safety g

Differentiable Efficient Operator Search

arXiv:2606.05232v1 Announce Type: cross Abstract: Efficient multimodal foundation models often rely on manually designed token-reduction operators, such as pruning, merging, pooling, and adaptive rewe

Local Ai

Efficient Asynchronous Federated Evaluation with Strategy Similarity Awareness for Intent-Based Networking in Industrial Internet of Things

arXiv:2512.20627v2 Announce Type: replace-cross Abstract: Intent-Based Networking (IBN) offers a promising paradigm for intelligent and automated network control in Industrial Internet of Things (IIoT

local-aiarxiv-cs-ai

Escaping the Verifier: Learning to Reason via Demonstrations

arXiv:2511.21667v4 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-w

HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation

arXiv:2602.07739v2 Announce Type: replace-cross Abstract: Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely

Hardware

Mac mini M4 vs Pc with Nvidia 5060 8gb for ai workloads?

The Mac mini M4 uses unified memory architecture where CPU and GPU share a single 24GB memory pool, while the RTX 5060 has dedicated VRAM. Mac mini M4 is preferred for large model inference (70B param

hardwarer-ollama

Local Ai

Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature

arXiv:2606.05206v1 Announce Type: cross Abstract: Fragmentation is common in interdisciplinary fields with diverse methods and theoretical commitments. Predictive coding neuroscience is a clear exampl

local-aiarxiv-cs-ai

PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluation

arXiv:2606.05697v1 Announce Type: new Abstract: User interface (UI) and user experience (UX) evaluation is central to product development, yet reliable feedback still relies on recruiting human partic

Tutorials

Pretraining Recurrent Networks without Recurrence

arXiv:2606.06479v1 Announce Type: cross Abstract: Training recurrent neural networks (RNNs) requires assigning credit across long sequences of computations. Standard backpropagation through time (BPTT

tutorialsarxiv-cs-ai