Search: “models”

Consistent Diffusion Language Models

arXiv:2605.00161v1 Announce Type: new Abstract: Diffusion language models (DLMs) are an attractive alternative to autoregressive models because they promise sublinear-time, parallel generation, yet pr

researcharxiv-cs-lg

4 May 2026

Local Ai

RadLite: Multi-Task LoRA Fine-Tuning of Small Language Models for CPU-Deployable Radiology AI

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2605.00421v1 Announce Type: new Abstract: Large language models (LLMs) show promise in radiology but their deployment is limited by computational requirements that preclude use in resource-const

local-aiarxiv-cs-cl

4 May 2026

The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning

arXiv:2603.17837v3 Announce Type: replace-cross Abstract: During conversational interactions, humans subconsciously engage in concurrent thinking while listening to a speaker. Although this internal c

researcharxiv-cs-cl

4 May 2026

CL-bench Life: Can Language Models Learn from Real-Life Context?

model-releasesarxiv-cs-cl

arXiv:2604.27043v1 Announce Type: new Abstract: Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for mode

1 May 2026

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed

arXiv:2512.14067v2 Announce Type: replace-cross Abstract: Diffusion language models (dLMs) have emerged as a promising paradigm that enables parallel, non-autoregressive generation, but their learning

1 May 2026

Cross-Domain Transfer of Hyperspectral Foundation Models

arXiv:2604.26478v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performanc

Goblin and related magical mentions were overrewarded in training, and the behavior was reinforced over successive models. We removed the go…

Goblin and related magical mentions were overrewarded in training, and the behavior was reinforced over successive models. We removed the goblin-affine reward signal for future models, and filtered tr

model-releasesopenai--x

LLM Psychosis: A Theoretical and Diagnostic Framework for Reality-Boundary Failures in Large Language Models

arXiv:2604.25934v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) as interactive agents has exposed a category of behavioral failure that prevailing terminology, princip

OpenAI says its models, starting with GPT-5.1, 'increasingly mentioned goblins, gremlins, and other creatures', leading to prompt instructions to mitigate it (OpenAI)

OpenAI: OpenAI says its models, starting with GPT-5.1, “increasingly mentioned goblins, gremlins, and other creatures”, leading to prompt instructions to mitigate it — Starting with GPT-5.1, our model

model-releasestechmeme

Time Blindness: Why Video-Language Models Can't See What Humans Can?

arXiv:2505.24867v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have made impressive strides in understanding spatio-temporal relationships in videos. Howeve

Safety

Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models

arXiv:2604.25072v1 Announce Type: new Abstract: Unified Multimodal Models (uMMs) aim to support both visual understanding and visual generation within a shared representation. However, existing evalua

safetyarxiv-cs-cv

Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts

arXiv:2410.06723v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) have emerged as powerful pretrained encoders for computational pathology, but their robustness under clinic

Tutorials

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds

arXiv:2604.25289v1 Announce Type: cross Abstract: Practically, training diffusion models typically requires explicit time conditioning to guide the network through the denoising sampling process. Espe

tutorialsarxiv-cs-cv

Principled Detection of Hallucinations in Large Language Models via Multiple Testing

arXiv:2508.18473v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have emerged as powerful foundational models to solve a variety of tasks, they have also been shown to be prone t

researcharxiv-cs-cl

Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening

model-releasesarxiv-cs-lg

arXiv:2604.23385v1 Announce Type: new Abstract: Transthoracic echocardiography is the reference standard for confirming structural heart disease (SHD), but first-line screening is limited by cost, wor

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models

arXiv:2502.04424v4 Announce Type: replace-cross Abstract: With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (E

feels like forever ago, but had to include openclaw in q1 trends coding models improved greatly in Q4 of 2025, early jan was ppl running cla…

model-releasesyohei-nakajima--x

feels like forever ago, but had to include openclaw in q1 trends coding models improved greatly in Q4 of 2025, early jan was ppl running claude codes in parallel, and clawdbot blew up late jan models

Impact of Age Specialized Models for Hypoglycemia Classification

arXiv:2604.23732v1 Announce Type: cross Abstract: Disease progression varies with age and is influenced by underlying genetic, biochemical, and hormonal etiologies, suggesting the need for tailored mo

KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models

arXiv:2603.01581v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models build a token-domain robot control paradigm, yet suffer from low speed. Speculative Decoding (SD) is an op

researcharxiv-cs-lg

Layerwise Convergence Fingerprints for Runtime Misbehavior Detection in Large Language Models

arXiv:2604.24542v1 Announce Type: cross Abstract: Large language models deployed at runtime can misbehave in ways that clean-data validation cannot anticipate: training-time backdoors lie dormant unti

Applications

M^2-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills

arXiv:2604.24182v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models predominantly rely on end-to-end fine-tuning. While effective, this paradigm compromises the inherent genera

applicationsarxiv-cs-ro

OpenClaw 2026.4.26 🦞 🎙️ Google Live Talk 🦙 Better Ollama/local models 🧳 Bring over Claude + Hermes setups 🔐 One-command Matrix E2EE Big…

OpenClaw 2026.4.26 🦞 🎙️ Google Live Talk 🦙 Better Ollama/local models 🧳 Bring over Claude + Hermes setups 🔐 One-command Matrix E2EE Big release. Local models eat well. https://github.com/openclaw/open

model-releasesollama--x

Using Language Models as Closed-Loop High-Level Planners for Robotics Applications: A Brief Overview and Benchmarks

arXiv:2511.07410v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Vision Language Models (VLMs) have become popular tools for embodied high-level planning. However, their depl

V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2509.14837v2 Announce Type: replace Abstract: Recent advances in causal interpretability have extended from language models to vision-language models (VLMs), seeking to reveal their internal mec

VAPO: End-to-end Slide-Enhanced Speech Recognition with Omni-modal Large Language Models

arXiv:2510.08618v2 Announce Type: replace-cross Abstract: Omni-modal large language models (OLLMs) offer a promising end-to-end solution for slide-enhanced speech recognition due to their inherent mul

Calibrating Behavioral Parameters with Large Language Models

arXiv:2602.01022v2 Announce Type: replace-cross Abstract: Behavioral parameters such as loss aversion, herding, and extrapolation are central to asset pricing models but remain difficult to measure re

27 Apr 2026

Large Language Models Decide Early and Explain Later

arXiv:2604.22266v1 Announce Type: new Abstract: Large Language Models often achieve strong performance by generating long intermediate chain-of-thought reasoning. However, it remains unclear when a mo

researcharxiv-cs-cl

27 Apr 2026

Mixed Membership sub-Gaussian Models

arXiv:2604.22633v1 Announce Type: cross Abstract: The Gaussian mixture model is widely used in unsupervised learning, owing to its simplicity and interpretability. However, a fundamental limitation of

researcharxiv-cs-lg

27 Apr 2026

Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers

arXiv:2507.15753v2 Announce Type: replace-cross Abstract: Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending

Context Unrolling in Omni Models

arXiv:2604.21921v1 Announce Type: new Abstract: We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representati

researcharxiv-cs-cv

DenoiseRank: Learning to Rank by Diffusion Models

arXiv:2604.20852v1 Announce Type: cross Abstract: Learning to rank (LTR) is one of the core tasks in Machine Learning. Traditional LTR models have made great progress, but nearly all of them are imple

Feature request for @huggingface - add a repository size option to the sort menu, I want to see the DeepSeek quantized models that take up t…

model-releasessimon-willison--x

Simon Willison requested that Hugging Face add a repository size sorting option to help users find and filter models by storage requirements, specifically mentioning interest in locating DeepSeek quan

GPT-5.5 is a giant leap forward for handling ambiguity compared to previous GPT models. As Windsurf 2.0 focuses more on parallel agents, thi…

model-releaseswindsurf--x

GPT-5.5 is a giant leap forward for handling ambiguity compared to previous GPT models. As Windsurf 2.0 focuses more on parallel agents, this model is key for long-horizon tasks — it excels at underst

Latent Denoising Improves Visual Alignment in Large Multimodal Models

arXiv:2604.21343v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) such as LLaVA are typically trained with an autoregressive language modeling objective, providing only indirect supervisi

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

arXiv:2604.21017v1 Announce Type: cross Abstract: Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precis

Process Supervision via Verbal Critique Improves Reasoning in Large Language Models

arXiv:2604.21611v1 Announce Type: cross Abstract: Inference-time scaling for LLM reasoning has focused on three axes: chain depth, sample breadth, and learned step-scorers (PRMs). We introduce a fourt

Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks

arXiv:2604.21041v1 Announce Type: new Abstract: Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining.

researcharxiv-cs-cv

Schoenfeld's Anatomy of Mathematical Reasoning by Language Models

arXiv:2512.19995v2 Announce Type: replace-cross Abstract: Large language models increasingly expose reasoning traces, yet their underlying cognitive structure and steps remain difficult to identify an

Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2604.21523v1 Announce Type: cross Abstract: Large Vision-Language Models (VLMs) are increasingly used to evaluate outputs of other models, for image-to-text (I2T) tasks such as visual question a

Thinking Like a Botanist: Challenging Multimodal Language Models with Intent-Driven Chain-of-Inquiry

arXiv:2604.20983v1 Announce Type: cross Abstract: Vision evaluations are typically done through multi-step processes. In most contemporary fields, experts analyze images using structured, evidence-bas

Transient Turn Injection: Exposing Stateless Multi-Turn Vulnerabilities in Large Language Models

arXiv:2604.21860v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This pape

Safety

Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models

arXiv:2604.20995v1 Announce Type: new Abstract: Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning

safetyarxiv-cs-ai

Assessing the Robustness of Climate Foundation Models under No-Analog Distribution Shifts

arXiv:2603.23043v2 Announce Type: replace-cross Abstract: The accelerating pace of climate change introduces profound non-stationarities that challenge the ability of Machine Learning based climate em

Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models

model-releasesarxiv-cs-lg

arXiv:2508.17761v3 Announce Type: replace Abstract: In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonl

ParetoSlider: Diffusion Models Post-Training for Continuous Reward Control

arXiv:2604.20816v1 Announce Type: cross Abstract: Reinforcement Learning (RL) post-training has become the standard for aligning generative models with human preferences, yet most methods rely on a si

researcharxiv-cs-cv

PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models

arXiv:2604.19773v1 Announce Type: cross Abstract: The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large langu

Hardware

Temporally Extended Mixture-of-Experts Models

arXiv:2604.20156v1 Announce Type: new Abstract: Mixture-of-Experts models, now popular for scaling capacity at fixed inference speed, switch experts at nearly every token. Once a model outgrows availa

hardwarearxiv-cs-lg

Safety

The Imperfective Paradox in Large Language Models

arXiv:2601.09373v2 Announce Type: replace Abstract: Do Large Language Models (LLMs) genuinely grasp the compositional semantics of events, or do they rely on surface-level probabilistic heuristics? We

safetyarxiv-cs-cl