model releases

Memory-Induced Tool-Drift in LLM Agents

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

Merch, on-premises. http://shop.cohere.com

Cohere announced merchandise available for purchase at their on-premises shop (shop.cohere.com), likely offering branded items such as apparel, stickers, or other company merchandise for employees, cu

model-releasescohere--x

26 May 2026

Merge-Bench: Resolve Merge Conflicts with Large Language Models

arXiv:2605.25890v1 Announce Type: new Abstract: This paper applies machine learning to the difficult and important task of version control merging. (1) We constructed a dataset, Merge-Bench, of 7938 r

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression

arXiv:2605.22337v2 Announce Type: replace Abstract: The KV cache used in large language models has linearly growing time complexity, so LLMs face memory blow-up and reduced decoding efficiency when th

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration

arXiv:2605.25030v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems offer a promising approach to reduce hallucinations and improve answer accuracy in large language models (L

MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

arXiv:2605.26006v1 Announce Type: cross Abstract: Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typic

MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding

arXiv:2605.24523v1 Announce Type: cross Abstract: Visual decoding from brain signals is a key challenge at the intersection of computer vision and neuroscience, requiring methods that bridge neural re

Minimax Limits of k-Fold Cross-Validation via Majority

arXiv:2605.25859v1 Announce Type: cross Abstract: We study the mean-squared error of k-fold cross-validation as a risk estimator, with particular emphasis on how its accuracy depends on the number of

Mistral-7B v0.3 at 128K in llama.cpp: 22,657 → 13,235 MiB live VRAM with ≤0.004 PPL drift

Mistral-7B v0.3 model achieves significant memory optimization when running at 128K context length in llama.cpp, reducing live VRAM usage from 22,657 MiB to 13,235 MiB while maintaining minimal perfor

model-releasesr-ollama

Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs

arXiv:2605.24681v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown great promise in multilingual machine translation (MT), even with limited bilingual supervision. However, fine

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

arXiv:2505.23764v3 Announce Type: replace-cross Abstract: Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the complex physical world. Existing benchmarks, h

Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending

arXiv:2605.25574v1 Announce Type: cross Abstract: Concept erasure has emerged as a key research direction for ensuring safe and ethical image synthesis in Text-to-Image (T2I) models. While existing st

MR-LiDAR: A Multi-Resolution Roadside LiDAR Benchmark for Perception Diagnostics and Deployment Guidance

arXiv:2605.24777v1 Announce Type: new Abstract: LiDAR model selection is a critical issue in roadside sensing systems, as it directly determines both perception capability and deployment cost. However

@mteamisloading the models from 6 months ago kinda feel the same like the recently released models. currently not holding my breath for more…

model-releasesjeremy-howard--x

Jeremy Howard comments that large language models released 6 months ago feel comparable in capability to recently released models, suggesting that the pace of improvement in model development may be s

MuCRASP: Multimodal Chain-of-thought Reasoning aware Structured Pruning

arXiv:2605.25842v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly rely on chain-of-thought (CoT) reasoning to solve complex multimodal tasks, but their large parameter sizes m

MuJoCoUni:Persistent Batched Runtime Primitives for MuJoCo

arXiv:2605.24922v1 Announce Type: new Abstract: We present MuJoCoUni, a downstream MuJoCo distribution for online robot learning and batched physics evaluation. Alongside the open-loop batched traject

MultiHaluDet: Multilingual Hallucination Detection via LLM Hidden State Probing

arXiv:2605.24919v1 Announce Type: new Abstract: Hallucinations in Large Language Models (LLMs) represent a critical barrier to their reliable deployment, a vulnerability heavily exacerbated in non-Eng

MuNet: A Mutualistic Network for Joint 3D Human Mesh Recovery and 3D Clothed Human Reconstruction from Single Images

arXiv:2605.25861v1 Announce Type: cross Abstract: 3D human mesh recovery and 3D clothed human reconstruction are inherently related, yet they have long been studied in isolation, thereby overlooking t

Muon in Associative Memory Learning: Training Dynamics and Scaling Laws

arXiv:2602.05725v2 Announce Type: replace Abstract: Muon updates matrix parameters via the matrix sign of the gradient and has shown strong empirical gains, yet its dynamics and scaling behavior remai

Neural Integral Operators for Inverse Problems: An Operator-Learning Framework for Small-Sample Spectroscopic Classification

arXiv:2505.03677v3 Announce Type: replace Abstract: Learning maps between function spaces with a strong inductive bias is a central challenge in soft computing, especially when training data are scarc

Neural Router: Semantic Content Matching for Agentic AI

arXiv:2605.25701v1 Announce Type: cross Abstract: Large language models (LLMs) can serve as the semantic-matching engine of a content-based publish/subscribe broker for agentic AI across the edge-clou

Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variables

arXiv:2605.25985v1 Announce Type: new Abstract: Complex Query Answering (CQA) is a fundamental knowledge representation and reasoning task over incomplete knowledge graphs (KGs). Answering existential

Neuromorphic LiDAR-based Bird's Eye View Object Detection using Energy-efficient Spiking Neural Networks

arXiv:2605.25293v1 Announce Type: cross Abstract: Autonomous driving perception demands accurate and efficient processing of three-dimensional sensor data under strict power constraints. Traditional c

Neurosymbolic AI is saving deep learning from hitting the wall (exactly as I said my 2022 paper “deep learning is hitting a wall”) Really …

model-releasesgary-marcus--x

Neurosymbolic AI is saving deep learning from hitting the wall (*exactly* as I said my 2022 paper “deep learning is hitting a wall”) Really sad to see someone as smart @peterwildeford confusing the or

New on the Engineering Blog: The access and permissions we grant agents should evolve with their capabilities. In our own products, we set t…

model-releasesboris-cherny--x

New on the Engineering Blog: The access and permissions we grant agents should evolve with their capabilities. In our own products, we set these parameters through sandboxing, which limits the scope o

Nine reasons why I warned OpenAI might fail and turn out to be the WeWork of AI, from two years ago.

model-releasesgary-marcus--x

Nine reasons why I warned OpenAI might fail and turn out to be the WeWork of AI, from two years ago. 9 reasons that OpenAI could someday be seen as the WeWork of AI: 👉 Lots of competitors are catching

Noise-Robust Financial Numerical Entity Attribute Tagging

arXiv:2605.24910v1 Announce Type: new Abstract: Financial Numerical Entity (FNE) understanding aims to recover the meaning of numerical mentions in financial reports. Existing studies primarily focus

Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent

arXiv:2605.25590v1 Announce Type: cross Abstract: We study nonstationary generalized linear bandits (GLBs), where the expected reward is modeled through a nonlinear link function with an unknown time-

NormimesDirection: Restoring the Missing Query Norm in Vision Linear Attention

arXiv:2506.21137v3 Announce Type: replace Abstract: Linear attention mitigates the quadratic complexity of softmax attention but suffers from a critical loss of expressiveness. We identify two primary

Novee debuts Agentic Fix, pushing pentest findings into Claude, Copilot and Cursor

model-releasessiliconangle

Artificial intelligence penetration testing startup Novee Cyber Security Ltd. today launched Agentic Fix, a new capability that pushes validated exploit findings directly into the AI coding agents dev

NVIDIA Vera CPU Is ‘Packing a Heavy-Hitting Punch’ Against Competition

model-releasesnvidia-blog

The shift to agentic AI creates a new CPU requirement for the AI factory: fast cores, massive memory bandwidth and the ability to sustain high performance when all cores are active. Initial benchmark

Omissive Bias in Religious Representation: Benchmarking LLM Answers to Everyday Ethical Decision-making

arXiv:2605.24319v1 Announce Type: new Abstract: As large language models become a default source of guidance on personal, moral, and existential questions, it matters whether they draw on the religiou

On the Epistemic Uncertainty of Overparametrized Neural Networks

arXiv:2605.25234v1 Announce Type: cross Abstract: Epistemic uncertainty is often viewed as a reducible uncertainty that vanishes with increasing data. This perspective implicitly assumes parameter ide

On the Sample Complexity of Robust Binary Hypothesis Testing

arXiv:2605.24741v1 Announce Type: cross Abstract: We study the sample complexity of robust binary hypothesis testing under three standard contamination models: arepsilon-additive (Huber), arepsilon-su

One-for-All Model Initialization with Frequency-Domain Knowledge

arXiv:2603.07523v2 Announce Type: replace Abstract: Transferring knowledge by fine-tuning large-scale pre-trained networks has become a standard paradigm for downstream tasks, yet the knowledge of a p

Optimizing Digital Therapeutic Interventions: Online Learning under Endogenous Adherence

arXiv:2605.24261v1 Announce Type: new Abstract: A critical challenge facing clinicians managing chronic disease interventions is sustaining long-run patient health given limited information and resour

ORACAL: A Robust and Explainable Multimodal Framework for Smart Contract Vulnerability Detection with Causal Graph Enrichment

arXiv:2603.28128v2 Announce Type: replace Abstract: Although Graph Neural Networks (GNNs) have shown promise for smart contract vulnerability detection, they still face significant limitations. Homoge

OrpQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization

arXiv:2605.26092v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) and Vision Transformers (ViTs) on edge devices is significantly constrained by memory limitations and t

OSDTW: Optimal Shared Depth and Task Weighting for Long-Tailed Recognition

arXiv:2605.24969v1 Announce Type: cross Abstract: Long-tailed recognition suffers from a persistent head--tail trade-off: improving tail performance often degrades head accuracy and can increase train

Our strategy lead @yeahfortommy was just on stage with CTO of @alibaba_cloud discussing Hermes Agent at the Qwen Conference, check it out: h…

model-releasesnous-research--x

Our strategy lead @yeahfortommy was just on stage with CTO of @alibaba_cloud discussing Hermes Agent at the Qwen Conference, check it out: https://www.youtube.com/live/r99c3sfgkmc?si=cnuR07ofhO_V69l-&

Overview of the PsyDefDetect Shared Task at BioNLP 2026: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations

arXiv:2605.24907v1 Announce Type: new Abstract: We present an overview of PsyDefDetect, the shared task on detecting levels of psychological defense mechanisms in emotional support dialogues, co-locat

PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization

arXiv:2605.06505v2 Announce Type: replace-cross Abstract: We introduce PACZero, a family of PAC-private zeroth-order mechanisms for fine-tuning large language models that delivers usable utility at I(

Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs

arXiv:2605.24154v1 Announce Type: new Abstract: Current safety alignment of foundation models largely follows a one-size-fits-all paradigm, applying the same refusal policy across users and contexts.

PALoRA: Projection-Adaptive LoRA for Preserving Reasoning in Large Language Models

arXiv:2605.24549v1 Announce Type: new Abstract: Efficiently updating Large Language Models (LLMs) with new or evolving factual knowledge remains a central challenge, as even parameter-efficient adapta

Parameter-Efficient CT Reconstruction via Deep Graph Laplacian Regularization

arXiv:2605.25348v1 Announce Type: cross Abstract: Low-dose computed tomography (LDCT) reconstruction faces a critical tradeoff between reconstruction quality and resource requirements. While recent de

Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection

arXiv:2605.23984v1 Announce Type: cross Abstract: Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogene

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering

arXiv:2605.24792v1 Announce Type: cross Abstract: The major limitations of gastrointestinal (GI) endoscopy AI systems arise from a shortage of annotated data, strict privacy policies, and significant

ParkourFormer: Integrating Predictive Supervision and Sequence Modeling into Parkour Locomotion

arXiv:2605.25782v1 Announce Type: new Abstract: Humanoid parkour requires locomotion policies to coordinate whole-body dynamics across rapidly changing terrains such as stairs, gaps, slopes, and obsta