Search: “models”

Contextuality from Single-State Ontological Models: An Information-Theoretic Obstruction

arXiv:2602.16716v3 Announce Type: replace Abstract: Contextuality is a central feature of quantum theory, traditionally understood as the impossibility of reproducing quantum measurement statistics us

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Edge-preserving noise for diffusion models

DGX agent

arXiv:2410.01540v4 Announce Type: replace Abstract: Classical diffusion models typically rely on isotropic Gaussian noise, treating all regions uniformly and overlooking structural information importa

researcharxiv-cs-cv

17 Apr 2026

Fact4ac at the Financial Misinformation Detection Challenge Task: Reference-Free Financial Misinformation Detection via Fine-Tuning and Few-Shot Prompting of Large Language Models

arXiv:2604.14640v1 Announce Type: new Abstract: The proliferation of financial misinformation poses a severe threat to market stability and investor trust, misleading market behavior and creating crit

GUI-Perturbed: Domain Randomization Reveals Systematic Brittleness in GUI Grounding Models

arXiv:2604.14262v1 Announce Type: new Abstract: GUI grounding models report over 85% accuracy on standard benchmarks, yet drop 27-56 percentage points when instructions require spatial reasoning rathe

researcharxiv-cs-lg

Local Ai

How to Disable Thinking mode of Ollama Models Using Copilot CLI?

A guide on disabling thinking mode in Ollama models using the CLI by running models with the `--think=false` flag or using `/set nothink` followed by a prompt. The post likely discusses how to configu

local-air-ollama

Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality

arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode

safetyarxiv-cs-cl

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems

arXiv:2601.14053v2 Announce Type: replace-cross Abstract: The field of artificial intelligence has undergone a revolution from foundational Transformer architectures to reasoning-capable systems appro

MetaDent: Labeling Clinical Images for Vision-Language Models in Dentistry

arXiv:2604.14866v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models

arXiv:2604.14672v1 Announce Type: new Abstract: Large language models (LLMs) are being increasingly used in urban planning, but since gendered space theory highlights how gender hierarchies are embedd

safetyarxiv-cs-cl

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models

arXiv:2604.14629v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable capabilities in joint vision-language understanding, but their large scale poses significant challen

safetyarxiv-cs-cv

Towards Fine-grained Temporal Perception: Post-Training Large Audio-Language Models with Audio-Side Time Prompt

arXiv:2604.13715v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) enable general audio understanding and demonstrate remarkable performance across various audio tasks. However, the

What folk don’t get is that the play of Anthropic et al is to get enterprises to use their models via their own wrapper hooked into systems …

model-releasesemad-mostaque--x

What folk don’t get is that the play of Anthropic et al is to get enterprises to use their models via their own wrapper hooked into systems of record This is why they are moving from per seat pricing

Beyond State Consistency: Behavior Consistency in Text-Based World Models

arXiv:2604.13824v1 Announce Type: new Abstract: World models have been emerging as critical components for assessing the consequences of actions generated by interactive agents in online planning and

safetyarxiv-cs-lg

Can Large Language Models Reliably Extract Physiology Index Values from Coronary Angiography Reports?

arXiv:2604.13077v1 Announce Type: new Abstract: Coronary angiography (CAG) reports contain clinically relevant physiological measurements, yet this information is typically in the form of unstructured

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

model-releasesarxiv-cs-lg

arXiv:2604.13882v1 Announce Type: new Abstract: The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread avail

F-Actor: Controllable Conversational Behaviour in Full-Duplex Models

arXiv:2601.11329v3 Announce Type: replace Abstract: Spoken conversational systems require more than accurate speech generation to have human-like conversations: to feel natural and engaging, they must

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding

arXiv:2604.13540v1 Announce Type: new Abstract: Unified Multimodal Models (UMMs) aim to integrate visual understanding and generation within a single structure. However, these models exhibit a notable

researcharxiv-cs-cv

Models are getting smaller, smarter and Apache licensed. Love to see Gemma and Qwen doing it.

Models are getting smaller, smarter and Apache licensed. Love to see Gemma and Qwen doing it. Qwen 3.6 is here, and open-source! Run it locally with improved agentic coding capabilities. Try it with C

model-releasesollama--x

Dreamer-CDP: Improving Reconstruction-free World Models Via Continuous Deterministic Representation Prediction

model-releasesarxiv-cs-lg

arXiv:2603.07083v2 Announce Type: replace Abstract: Model-based reinforcement learning (MBRL) agents operating in high-dimensional observation spaces, such as Dreamer, rely on learning abstract repres

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning

arXiv:2409.06679v3 Announce Type: replace Abstract: Processing long contexts is increasingly important for Large Language Models (LLMs) in tasks like multi-turn dialogues, code generation, and documen

researcharxiv-cs-cl

KumoRFM-2: Scaling Foundation Models for Relational Learning

arXiv:2604.12596v1 Announce Type: cross Abstract: We introduce KumoRFM-2, the next iteration of a pre-trained foundation model for relational data. KumoRFM-2 supports in-context learning as well as fi

Large Language Models are Powerful Electronic Health Record Encoders

arXiv:2502.17403v5 Announce Type: replace-cross Abstract: Electronic Health Records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge tradit

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models

arXiv:2507.22359v4 Announce Type: replace Abstract: Although large language models (LLMs) have shown exceptional capabilities across a wide range of tasks, reliable evaluation remains a critical chall

My bets on open models, mid-2026

A mid-2026 outlook piece from the Interconnects AI newsletter in which the author makes specific predictions about the trajectory of open-weight language models, likely covering expected capability mi

researchinterconnects

Scaling Exposes the Trigger: Input-Level Backdoor Detection in Text-to-Image Diffusion Models via Cross-Attention Scaling

arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i

researcharxiv-cs-cv

Agents

Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves colle…

Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves collecting data, diagnosing failures, building evals, avoiding re

agentsdair-ai--x

SOAR: Self-Correction for Optimal Alignment and Refinement in Diffusion Models

arXiv:2604.12617v1 Announce Type: cross Abstract: The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SFT) on curated data and reinforcement learning (RL)

Local Ai

Towards Interpretable Foundation Models for Retinal Fundus Images

arXiv:2603.18846v2 Announce Type: replace Abstract: Foundation models are used to extract transferable representations from large amounts of unlabeled data, typically via self-supervised learning (SSL

local-aiarxiv-cs-cv

Local Ai

What does 'Run <number> cloud models at a time' in Ollama Cloud Subscription mean?

The Ollama Cloud Subscription includes a feature described as 'Run cloud models at a time,' which refers to how many AI models a user can have simultaneously loaded and running in the cloud at any giv

local-air-ollama

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation

arXiv:2504.14988v3 Announce Type: replace Abstract: Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated remarkable multimodal perception capabilities, garnering significant a

COREY: A Prototype Study of Entropy-Guided Operator Fusion with Hadamard Reparameterization for Selective State Space Models

arXiv:2604.10597v1 Announce Type: cross Abstract: State Space Models (SSMs), represented by the Mamba family, provide linear-time sequence modeling and are attractive for long-context inference. Yet p

Data-Efficient Surgical Phase Segmentation in Small-Incision Cataract Surgery: A Controlled Study of Vision Foundation Models

arXiv:2604.10514v1 Announce Type: cross Abstract: Surgical phase segmentation is central to computer-assisted surgery, yet robust models remain difficult to develop when labeled surgical videos are sc

Demographic and Linguistic Bias Evaluation in Omnimodal Language Models

arXiv:2604.10014v1 Announce Type: cross Abstract: This paper provides a comprehensive evaluation of demographic and linguistic biases in omnimodal language models that process text, images, audio, and

Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models

arXiv:2604.10567v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to autoregressive language models, offering the potential for parallel

Finetune Like You Pretrain: Boosting Zero-shot Adversarial Robustness in Vision-language Models

arXiv:2604.11576v1 Announce Type: new Abstract: Despite their impressive zero-shot abilities, vision-language models such as CLIP have been shown to be susceptible to adversarial attacks. To enhance i

FPBench: A Comprehensive Benchmark of Multimodal Large Language Models for Fingerprint Analysis

arXiv:2512.18073v2 Announce Type: replace Abstract: Multimodal LLMs (MLLMs) are capable of performing complex data analysis, visual question answering, generation, and reasoning tasks. However, their

From Topology to Trajectory: LLM-Driven World Models For Supply Chain Resilience

arXiv:2604.11041v1 Announce Type: new Abstract: Semiconductor supply chains face unprecedented resilience challenges amidst global geopolitical turbulence. Conventional Large Language Model (LLM) plan

GeoMeld: Toward Semantically Grounded Foundation Models for Remote Sensing

arXiv:2604.10591v1 Announce Type: cross Abstract: Effective foundation modeling in remote sensing requires spatially aligned heterogeneous modalities coupled with semantically grounded supervision, ye

Measuring the Authority Stack of AI Systems: Empirical Analysis of 366,120 Forced-Choice Responses Across 8 AI Models

arXiv:2604.11216v1 Announce Type: new Abstract: What values, evidence preferences, and source trust hierarchies do AI systems actually exhibit when facing structured dilemmas? We present the first lar

MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models

arXiv:2602.21950v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world

METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models

arXiv:2604.11502v1 Announce Type: cross Abstract: Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate th

MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models

arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio

Hardware

Nvidia unveils Ising AI models for quantum error correction and calibration

Technology and computing giant Nvidia Corp. today announced the release of Ising, the world’s first open artificial intelligence model family aimed at quantum computing calibration and error correctio

hardwaresiliconangle

OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language World Models

arXiv:2604.10866v1 Announce Type: new Abstract: AI agents are expected to perform professional work across hundreds of occupational domains (from emergency department triage to nuclear reactor safety

Physics and causally constrained discrete-time neural models of turbulent dynamical systems

arXiv:2602.13847v3 Announce Type: replace-cross Abstract: We present a framework for constructing physics and causally constrained neural models of turbulent dynamical systems from data. We first form

researcharxiv-cs-lg

Resource Consumption Threats in Large Language Models

arXiv:2603.16068v3 Announce Type: replace-cross Abstract: Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LL

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i

Agents

The future is open. At GTC Live, @cohere Co-founder & CEO, Aidan Gomez describes how open models give developers the autonomy they need to s…

The future is open. At GTC Live, @cohere Co-founder & CEO, Aidan Gomez describes how open models give developers the autonomy they need to scale 📈, customize and innovate their way into the future of

agentscohere--x