model releases

FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning

arXiv:2605.22869v1 Announce Type: new Abstract: Both full fine-tuning (Full FT) and parameter-efficient fine-tuning methods such as LoRA introduce weight updates without accounting for the spectral st

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GENSTRAT: Toward a Science of Strategic Reasoning in Large Language Models

DGX agent

arXiv:2605.23238v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as economic agents in marketplaces, auctions, and bidding settings. Anticipating their behavior i

model-releasesarxiv-cs-ai

25 May 2026

Given how much of the original 'bottle of water per generated email' water estimate came from guesses at the architecture of GPT-4, it would…

model-releasessimon-willison--x

Given how much of the original 'bottle of water per generated email' water estimate came from guesses at the architecture of GPT-4, it would be very much in @OpenAI's interest to publish the architect

. @GrooveJonesXR needed to deliver the impossible: giant NFL-licensed Crocs parachuting into Dick's Sporting Goods parking lots; hyper-reali…

. @GrooveJonesXR needed to deliver the impossible: giant NFL-licensed Crocs parachuting into Dick's Sporting Goods parking lots; hyper-realistic, multi-location, vertical 9:16 on a holiday deadline. A

model-releasescomfyui--x

GT-HarmBench: Benchmarking AI Safety Risks Through the Lens of Game Theory

arXiv:2602.12316v2 Announce Type: replace Abstract: Frontier AI systems are increasingly capable and deployed in high-stakes multi-agent environments. However, existing AI safety benchmarks largely ev

HARNESS-LM: A Three-Phase Training Recipe for Harnessing SLMs in Sponsored Search Retrieval

arXiv:2605.23572v1 Announce Type: cross Abstract: In the competitive landscape of sponsored search, balancing retrieval quality with production latency is a critical challenge. While large retrieval m

Hermes Agent now can orchestrate the @OpenHandsDev agents with a new optional skill! `hermes update` then do `hermes skills install official…

model-releasesnous-research--x

Hermes Agent now can orchestrate the @OpenHandsDev agents with a new optional skill! `hermes update` then do `hermes skills install official/autonomous-ai-agents/openhands` Reminder: You can already d

Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence

arXiv:2605.23821v1 Announce Type: new Abstract: We propose a distributional theory of how hypernymy -- the ``is-a'' relation between general and specific concepts -- is encoded geometrically in langua

How Far Are We from Generating Missing Modalities with Foundation Models?

arXiv:2506.03530v3 Announce Type: replace-cross Abstract: Multimodal foundation models have demonstrated impressive capabilities across diverse tasks. However, their potential as plug-and-play solutio

How Hard is it to Rig a Benchmark? A Social Choice Analysis of Leaderboard Robustness

arXiv:2605.23628v1 Announce Type: new Abstract: Multi-task benchmarks have become a central pillar of machine learning research, yet their growing influence has incentivised benchmark gaming -- strate

HTMuon: Improving Muon via Heavy-Tailed Spectral Correction

arXiv:2603.10067v2 Announce Type: replace-cross Abstract: Muon has recently shown promising results in LLM training. In this work, we study how to further improve Muon. We argue that Muon's orthogonal

Human-Centered Learning Mechanics: A Dynamical Framework for Entropy-Regulated Representation Learning

arXiv:2605.22940v1 Announce Type: cross Abstract: Deep learning is increasingly viewed as a dynamical process in parameter space, yet many existing theories still treat training as a closed optimizati

✅Implicit caching is now live on Qwen3.7-Max — kicks in automatically, no setup needed. ⚡️Faster + cheaper out of the box. Need higher, more…

✅Implicit caching is now live on Qwen3.7-Max — kicks in automatically, no setup needed. ⚡️Faster + cheaper out of the box. Need higher, more deterministic hit rates? Try explicit caching instead. 🙌 🔗B

model-releasesqwen--x

ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization

arXiv:2605.22885v1 Announce Type: new Abstract: Formal mathematics libraries are rapidly expanding, creating a growing need to refactor verified proofs for maintainability and to improve training data

In his ~43,000-word encyclical, the Pope urged governments to slow down AI development and decried 'new forms of slavery' in AI and tech supply chains (Joshua McElwee/Reuters)

Joshua McElwee / Reuters: In his ~43,000-word encyclical, the Pope urged governments to slow down AI development and decried “new forms of slavery” in AI and tech supply chains — Pope Leo urged govern

model-releasestechmeme

Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems

arXiv:2605.23109v1 Announce Type: new Abstract: AI agents increasingly excel at generating, testing, and refining code. However, they fall short on tasks requiring formal guarantees of full coverage t

IntentionNav: A Benchmark for Intent-Driven Object Navigation from Implicit Human Instruction

model-releasesarxiv-cs-cv

arXiv:2605.23187v1 Announce Type: new Abstract: Existing object navigation benchmarks usually tell an embodied agent which object category to find, such as microwave or chair. Human-facing embodied AI

Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures

arXiv:2511.03882v2 Announce Type: replace-cross Abstract: Imitation learning-based robot control policies are enjoying renewed interest in video-based robotics. However, it remains unclear whether thi

Is Capability a Liability? More Capable Language Models Make Worse Forecasts When It Matters Most

arXiv:2605.22672v2 Announce Type: replace Abstract: We document inverse scaling in LLMs on forecasting problems whose underlying time series exhibit superlinear growth and tail risk of regime change,

It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt

arXiv:2605.23825v1 Announce Type: cross Abstract: It has generally been assumed that geopolitical bias in language models originates from the training data used during the pre-training phase. We teste

I’ve just released MiMo V2.5-Coder. If you have 128 GB of RAM, this is one of the best models you can run locally. It’s fast, and in all my …

model-releasesclem-delangue--x

I’ve just released MiMo V2.5-Coder. If you have 128 GB of RAM, this is one of the best models you can run locally. It’s fast, and in all my experiments it outperformed Qwen 3.6 and DeepSeek 4-Flash. h

Joint Model Parameter Scaling and Universal-Domain Data Integration for E-commerce Search Ranking

arXiv:2603.24226v3 Announce Type: replace-cross Abstract: Scaling studies for industrial search, advertising, and recommendation have largely emphasized enlarging model capacity or refining architectu

Just found that if you scroll down in the Claude Code app on iPhone… Clawd starts jumping and walking around looking for apps to build

model-releasesboris-cherny--x

The Claude Code app for iPhone features an interactive Easter egg where scrolling down triggers an animated character named 'Clawd' that jumps and walks around the screen, appearing to search for apps

Just spent a full coding session with Grok Build and honestly? It's right there with Claude. The model is sharp, the agentic flow holds up o…

model-releaseselon-musk--x

Just spent a full coding session with Grok Build and honestly? It's right there with Claude. The model is sharp, the agentic flow holds up on complex tasks, and it has actual personality. Few rough ed

KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis

arXiv:2605.23082v1 Announce Type: cross Abstract: Survival analysis aims to model how covariates and time jointly shape the time-to-event distribution under right censoring. Classical methods such as

L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark

arXiv:2605.22893v1 Announce Type: cross Abstract: We introduce a novel Longitudinal Focused Attention Meditation Electroencephalography (L-FAME) dataset and an accompanying benchmark, designed to fost

Learning Safely Without Knowing the World:COMPASS-Hedge

arXiv:2603.22348v3 Announce Type: replace Abstract: Online learning algorithms often face a fundamental trilemma: balancing regret guarantees between adversarial and stochastic settings and providing

LFRAG: Layout-oriented Fine-grained Retrieval-Augmented Generation on Multimodal Document Understanding

arXiv:2605.22829v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for enhancing Large Language Models (LLMs) with external knowledg

Lipschitz Optimization for Formal Verification of Homographies

arXiv:2605.23203v1 Announce Type: cross Abstract: The adoption of vision neural networks in regulated industries requires formal robustness guarantees, especially in safety-critical domains such as he

LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics

arXiv:2601.18685v3 Announce Type: replace-cross Abstract: The capabilities of generative AI in mathematics education are rapidly evolving, posing significant challenges for research to keep pace. Rese

LLM-driven design of physics-constrained constitutive models: two agents are better than one

arXiv:2605.23754v1 Announce Type: new Abstract: Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics

LQ-rPPG: A Label-Quantized Coarse-to-Fine Learning Framework for Remote Physiological Measurement

model-releasesarxiv-cs-cv

arXiv:2605.23174v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact measurement of physiological signals from facial videos, offering strong potential for remote hea

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models

arXiv:2605.23007v1 Announce Type: cross Abstract: We explore the application of LLM-driven algorithm optimization to several common tasks in quantitative finance. MadEvolve, a general-purpose algorith

MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks

arXiv:2601.14652v5 Announce Type: replace Abstract: While multi-agent systems (MAS) promise elevated intelligence through coordination of agents, current approaches to automatic MAS design under-deliv

MedExpMem: Adapting Experience Memory for Differential Diagnosis

arXiv:2605.22872v1 Announce Type: cross Abstract: Experienced physicians develop diagnostic expertise through clinical practice, acquiring not only disease knowledge but also the ability to differenti

MELT: A Behavioral Trace Dataset for High-Risk Memecoin Launch Detection

arXiv:2602.13480v2 Announce Type: cross Abstract: Launchpads have become the dominant mechanism for issuing memecoins, exposing investors to a new class of high-risk launches that existing rug-pull de

Memorization Dynamics of Fill-in-the-Middle Pretraining

arXiv:2605.22981v1 Announce Type: cross Abstract: Fill-in-the-middle (FIM) is a pretraining objective widely used to equip causal language models with infilling ability, yet its effect on verbatim mem

Metadata Predictability Is Not Evidence Dependence: An Intervention-Based Audit for Weak-Label Benchmarks

arXiv:2605.23701v1 Announce Type: new Abstract: We study a protocol-level test for weak-label benchmarks: whether benchmark outputs change when the provided evidence is intervened on. Metadata-only sh

Model Collapse as Cultural Evolution

arXiv:2605.23054v1 Announce Type: cross Abstract: Model collapse, the progressive degradation of LLMs trained on their own outputs, has been characterized statistically but lacks a linguistic explanat

ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU

arXiv:2605.23057v1 Announce Type: cross Abstract: ModeSwitch-LLM is a lightweight request-boundary controller for improving single-GPU large language model inference efficiency by routing each request

Moonwalk: Inverse-Forward Differentiation

arXiv:2402.14212v4 Announce Type: replace-cross Abstract: Backpropagation's main limitation is its need to store intermediate activations (residuals) during the forward pass, which restricts the depth

Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer

arXiv:2605.23871v1 Announce Type: cross Abstract: We develop a gradient flow on the space of probability measures defined on matrix-valued parameters induced by regularized Muon, an analytically smoot

Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models

arXiv:2505.17015v2 Announce Type: replace-cross Abstract: Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single ima

Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection

arXiv:2605.23036v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) enable feature-level mechanistic interpretability and activation steering in large language models (LLMs), but SAE-based lang

Non-normal spectral signatures of instability in neural network training dynamics

arXiv:2605.23476v1 Announce Type: new Abstract: Training instabilities in deep networks - loss spikes, oscillatory convergence, and gradient pathologies - are empirically prevalent but lack a rigorous

NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion

model-releasesarxiv-cs-cv

arXiv:2511.11051v3 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) fusion enables the composition of subject and style representations for controllable generation without retraining. Howev

One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents

arXiv:2605.23652v1 Announce Type: new Abstract: On a 300-persona life-simulation benchmark, pcsp achieves compositional zero-shot persona identification up to 17x above chance, Spearman rho approx 0.7

Online Partitioned Local Depth for semi-supervised applications

arXiv:2512.15436v2 Announce Type: replace-cross Abstract: We introduce an extension of the partitioned local depth (PaLD) algorithm that is adapted to online applications such as semi-supervised predi