model releases

BOHM: Zero-Cost Hierarchical Attribution for Compound AI Systems

arXiv:2605.22866v1 Announce Type: new Abstract: Compound AI systems route tasks through hierarchies of specialised components. Attribution is dominated by Shapley-based methods (SHAP), which decompose

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Brain-LLM Alignment Tracks Training Data, Not Typology

DGX agent

arXiv:2605.23032v1 Announce Type: cross Abstract: Brain-LLM alignment is well established in English, yet the brain's language network is neuroanatomically universal across languages. Does alignment a

model-releasesarxiv-cs-ai

25 May 2026

BURMESE-SAN: Burmese NLP Benchmark for Evaluating Large Language Models

arXiv:2602.18788v3 Announce Type: replace Abstract: We introduce BURMESE-SAN, the first holistic benchmark that systematically evaluates large language models (LLMs) for Burmese across three core NLP

Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs

arXiv:2605.22971v1 Announce Type: new Abstract: Employees often struggle to identify ``who knows what,'' leading to organizational productivity losses. We investigate whether Large Language Models (LL

Canadians be like come to our Toronto tech week party

Toronto Tech Week is an annual event in Toronto, Canada that brings together technology professionals, entrepreneurs, and innovators for networking, learning, and celebration of the local tech ecosyst

model-releasescohere--x

CARE: Class-Adaptive Expert Consensus for Reliable Learning with Long-Tailed Noisy Labels

arXiv:2605.23254v1 Announce Type: new Abstract: Learning from real-world data is frequently hindered by the compound challenge of long-tailed class distributions and noisy annotations. Existing method

CaST-Bench: Benchmarking Causal Chain-Grounded Spatio-Temporal Reasoning for Video Question Answering

arXiv:2605.23216v1 Announce Type: new Abstract: Cause-and-effect reasoning in video is a significant challenge for Vision-Language Models (VLMs), as it requires going beyond surface-level perception t

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models

arXiv:2605.23694v1 Announce Type: new Abstract: Chart descriptions are essential for accessibility, cross-modal retrieval, and assisting readers in extracting insights from complex visualizations. As

CHRONOS: Temporally-Aware Multi-Agent Coordination for Evolving Data Marketplaces

arXiv:2605.23887v1 Announce Type: cross Abstract: Temporal knowledge-graph data marketplaces face three coupled failures in static designs: stale hybrid index shortcuts reduce recall as edges evolve,

ComfyUI-Angelo now supports Qwen Edit

model-releasesr-stablediffusion

ComfyUI-Angelo now supports Qwen-Image-Edit, an advanced image editing model that provides text editing features and the ability to edit both semantics and appearance of images. The model applies Qwen

Complete-muE: Optimal Hyperparameter Transfer and Scaling for MoE Models

arXiv:2605.23893v1 Announce Type: new Abstract: We propose Complete-muE, a framework which targets hyperparameter transfer across dense FFN and any Mixture-of-Experts (MoE) setups in transformer block

Computable Fairness: Boltzmann-Softmax Control for AI Resource Allocation

arXiv:2605.22827v1 Announce Type: cross Abstract: In large-scale AI systems, allocating scarce resources such as GPU compute time and bandwidth among multiple agents is a critical challenge. Conventio

Convex Optimization for Alignment and Preference Learning on a Single GPU

arXiv:2605.23244v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) to align with human preferences has driven the success of systems such as Gemini and ChatGPT. However, approach

Cost-Effective Model Evaluation with Meta-Learning

arXiv:2605.23595v1 Announce Type: cross Abstract: The rapid growth of machine learning has produced an ever-expanding ecosystem of models, making it increasingly challenging to verify the reliability

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization

arXiv:2605.23391v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) for coupled multiphysics systems suffer systematic accuracy degradation as inter-equation coupling strengthens.

CRONOS: Benchmarking Counterfactual Physical Consistency in Video Models

arXiv:2605.23699v1 Announce Type: new Abstract: Video prediction is increasingly viewed as a path toward generalizable world models, yet it remains unclear whether these systems learn underlying causa

Cultural Adaptation in Large Language Models for Political Discourse

arXiv:2605.23332v1 Announce Type: new Abstract: The integration of large language models into political discourse analysis creates new opportunities for comparative research, policy analysis, and civi

CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception

arXiv:2605.23655v1 Announce Type: cross Abstract: High-resolution (HR) image perception presents a key bottleneck for multimodal large language models (MLLMs). While visual search offers a promising s

D2 Actor Critic: Diffusion Actor Meets Distributional Critic

arXiv:2510.03508v3 Announce Type: replace Abstract: We introduce D2AC, a new model-free reinforcement learning (RL) algorithm designed to train expressive diffusion policies online effectively. At its

DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures

arXiv:2511.15503v2 Announce Type: replace-cross Abstract: High-performance Host processors can integrate Processing-In-Memory (PIM) devices, which can accelerate memory-intensive kernels of Machine Le

DDX-TRACE: A Benchmark for Medical Diagnostic Trajectories in VLMs

arXiv:2605.23629v1 Announce Type: new Abstract: Medical diagnosis is not a single prediction from a fully specified vignette. It is a sequential workup: clinicians decide what evidence to obtain, revi

Decomposing and Measuring Evaluation Awareness

arXiv:2605.23055v1 Announce Type: cross Abstract: Frontier language models sometimes recognize that they are being evaluated and adjust their behavior, undermining validity of benchmark results. Yet t

Decomposing Queries into Tool Calls for Long-Video Keyframe Retrieval

arXiv:2605.23826v1 Announce Type: cross Abstract: Keyframe selection is a direct way to provide verifiable visual evidence for long-video question answering (QA). Queries differ in what they require,

Decomposition-Based Modular Conformal Prediction for Two-Stage Modeling

arXiv:2510.04406v2 Announce Type: replace-cross Abstract: Conformal prediction offers finite-sample coverage guarantees under minimal assumptions. However, existing methods treat the entire modeling p

Decoupling Spatio-Temporal Adapter for Fine-Grained Badminton Action Localization

arXiv:2605.23355v1 Announce Type: new Abstract: Temporal Action Localization (TAL) has been extensively studied in generic video understanding, while fine-grained sports scenarios, such as professiona

DeepSeek V4 Flash IS BACK on Nous Portal for FREE for use in Hermes Agent! Check it out at https://portal.nousresearch.com/manage-subscripti…

model-releasesnous-research--x

DeepSeek V4 Flash model has been made available again on the Nous Research portal at no cost for use with Hermes Agent applications. Users can access and utilize this model through the Nous portal's s

DepthAgent: Towards Better Universal Depth Estimation via Sample-wise Expert Selection

arXiv:2605.23281v1 Announce Type: new Abstract: Monocular metric depth estimation has achieved strong progress with large-scale training and universal-camera modeling, yet robust deployment across div

Design and Report Benchmarks for Knowledge Work

arXiv:2605.23262v1 Announce Type: new Abstract: The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowl

DFKI-MLT at SemEval-2026 TASK 7: Steering Multilingual Models Towards Cultural Knowledge

arXiv:2605.23069v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used across diverse linguistic and cultural contexts, yet their cultural knowledge remains uneven across r

Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation

arXiv:2605.22950v1 Announce Type: cross Abstract: Score matching is an alternative to maximum likelihood estimation when the normalizing constant is unknown or too costly to evaluate. However, vanilla

Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring

arXiv:2605.23282v1 Announce Type: cross Abstract: Defocus deblurring in pathological microscopy remains challenging due to the spatially varying and locally discontinuous nature of optical blur induce

Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025

arXiv:2605.23094v1 Announce Type: cross Abstract: Generative augmentation is often proposed as a remedy for small medical-image datasets, but synthetic images are only useful when they improve downstr

DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods

arXiv:2605.23052v1 Announce Type: cross Abstract: We present DreamerNLplus, a hybrid framework for modeling mental health dynamics from social media timelines in the CLPsych 2026 shared task. Our syst

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving

arXiv:2605.23176v1 Announce Type: new Abstract: Spatiotemporal intelligence in autonomous driving (AD) requires an agent to integrate multi-view observations into a coherent scene representation, main

Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning

arXiv:2509.26383v5 Announce Type: replace-cross Abstract: Knowledge-graph retrieval-augmented generation (KG-RAG) couples large language models (LLMs) with structured, verifiable knowledge graphs (KGs

Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries

arXiv:2404.05108v3 Announce Type: replace-cross Abstract: Gradient estimation is a central challenge in training parameterized quantum circuits (PQCs) for hybrid quantum-classical optimization and lea

Efficient One-Step Diffusion Restoration Model with Compact Token Compression and Linear Attention

arXiv:2605.23451v1 Announce Type: new Abstract: Real-world image super-resolution aims to recover high-quality images from complex and unknown real-world degradations. However, existing generative Rea

Entropy Equivalence Testing

arXiv:2605.23225v1 Announce Type: cross Abstract: We introduce the problem of entropy equivalence testing for probability distributions, a relaxation of the well-studied closeness testing problem, whe

ETCHR: Editing To Clarify and Harness Reasoning

arXiv:2605.23897v1 Announce Type: cross Abstract: Multimodal Large Language Models have advanced visual reasoning, yet a purely textual chain of thought remains a bottleneck for questions that require

Evaluating Large Language Models in a Complex Hidden Role Game

arXiv:2605.22826v1 Announce Type: cross Abstract: Quantifying the deceptive potential of Large Language Models (LLMs) is critical for AI safety, yet difficult to achieve in uncontrolled environments.

Evaluating Memory Structure in LLM Agents

arXiv:2602.11243v2 Announce Type: replace-cross Abstract: Modern LLM-based agents and chat assistants rely on long-term memory frameworks to store reusable knowledge, recall user preferences, and augm

Exploitation of KnowledgeDeliver via ViewState Deserialization Vulnerability

model-releasesgoogle-cloud-ai

Written by: Takahiro Sugiyama, Peter Revelant, Mathew Potaczek Introduction In late 2025, Mandiant responded to a security incident involving a compromised web server running KnowledgeDeliver. Knowled

Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking

arXiv:2605.23118v1 Announce Type: cross Abstract: Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-of

Exploring deep learning for Event-Based Saliency Prediction with a Transformer-based model

arXiv:2605.23790v1 Announce Type: new Abstract: Saliency prediction has been extensively studied in RGB images and videos as a computational model of human visual attention. In contrast, predicting sa

FAST-ME: Foundation-aware Adaptive Stopping for Motion Estimation for Efficient IoT Video Analysis

arXiv:2605.23428v1 Announce Type: new Abstract: In modern multimedia systems, efficient video processing is critical, especially in resource-constrained environments such as IoT-based camera networks,

FastKernels: Benchmarking GPU Kernel Generation in Production

arXiv:2605.23215v1 Announce Type: cross Abstract: LLM-based agents for GPU kernel generation are advancing rapidly, yet their progress is fundamentally constrained by the benchmarks they optimize agai

FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation

arXiv:2510.08945v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has emerged as a promising paradigm for improving factual accuracy in large language models (LLMs). We introduc

Fine-Tuning Causal LLMs for Text Classification: Embedding-Based vs. Instruction-Based Approaches

arXiv:2512.12677v2 Announce Type: replace-cross Abstract: We explore efficient strategies to fine-tune decoder-only Large Language Models (LLMs) for downstream text classification under resource const