Search: “models”

Higher-order pruning of experts in mixture-of-experts language models

arXiv:2609.18916v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models suffer from large parameter counts, which create a significant memory bottleneck. Expert pruning is the most

17 Sept 2026

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Research

The Mirage of Calibrated Confidence: Trajectory-Independence of Verbalized Confidence in Vision-Language Models

DGX agent

arXiv:2609.18453v1 Announce Type: new Abstract: A calibrated Vision-Language Model (VLM) can repeatedly self-correct, say 'Wait, I should recheck,' arrive at the wrong answer, and still report high co

researcharxiv-cs-ai

17 Sept 2026

BrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Models

arXiv:2609.17443v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual question answering (VQA) performance, but processing large cluttered images is computationally expen

16 Sept 2026

Certified Uncertainty Propagation in One-Shot Federated Bayesian Models via Posterior Event Transport

arXiv:2609.16373v1 Announce Type: new Abstract: Probabilistic certification of Bayesian neural networks lower-bounds the posterior probability that a model satisfies a verifier-defined safety property

16 Sept 2026

ViD: Vision-Dominant Gender Bias Mitigation for Large Vision-Language Models

arXiv:2609.16647v1 Announce Type: new Abstract: Gender bias in large vision-language models (LVLMs) undermines their fairness and reliability, compromising output trustworthiness. Current mitigation m

16 Sept 2026

Artificial entrepreneurial cognition: Locating and causally steering an opportunity recognition dial inside large language models (LLMs)

arXiv:2609.15277v1 Announce Type: new Abstract: Entrepreneurial cognition is a foundation of entrepreneurship research. Yet the growing involvement of large language models (LLMs) in entrepreneurial w

Bridging the Gap in ECG-Based Emotion Recognition: A Unified Evaluation of Deep Learning Models

arXiv:2609.15055v1 Announce Type: cross Abstract: Deep learning has led to numerous proposed architectures for Automated Emotion Recognition (AER) from electrocardiogram (ECG) data, but inconsistencie

Context-Dependent Affordance Reports in Vision-Language Models

arXiv:2603.04419v3 Announce Type: replace-cross Abstract: Vision-language models produce different object and use descriptions under different persona prompts, but low overlap alone does not identify

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

From Density to Biopsy Decisions and Malignancy Prediction: A Benchmark Study of Multimodal Large Language Models Against Radiologists in Digital and Contrast-Enhanced Mammography

arXiv:2609.14676v1 Announce Type: new Abstract: Purpose: To compare four multimodal large language models (MLLMs) with radiologists of varying expertise in breast density assessment, BI-RADS assessmen

Machine learning-assisted calibration of Agent-based Models: surrogate-based optimization with Genetic Algorithm and Particle Swarm Optimization

arXiv:2609.13247v1 Announce Type: cross Abstract: Calibrating an agent-based model (ABM) is difficult because its objective landscape is stochastic and rugged, and can be evaluated only through costly

MANAS-2: Constrained Reconstruction for EEG Foundation Models

arXiv:2609.13717v1 Announce Type: new Abstract: Masked reconstruction is widely used for EEG foundation models, but optimizing reconstruction on low-SNR waveforms does not necessarily produce the most

researcharxiv-cs-ai

Multimodal Foundation Models Adaptation based on Domain-Aware Relaxed Orthogonal Subspace for Remote Sensing

arXiv:2609.13654v1 Announce Type: new Abstract: Pretrained foundation models (FMs) have achieved remarkable success in computer vision, yet their high fine-tuning cost limits practical deployment. Par

Industry

OpenRouter users spent more on OpenAI's models than on Anthropic's in the week of September 7, the first time that happened since the week of February 26, 2024 (@openrouter)

@openrouter: OpenRouter users spent more on OpenAI's models than on Anthropic's in the week of September 7, the first time that happened since the week of February 26, 2024 — OpenRouter users spent mo

industrytechmeme

Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT

arXiv:2609.14106v1 Announce Type: new Abstract: We evaluated parameter-efficient fine-tuning (PEFT) of the Segment Anything Model (SAM) for liver tumor segmentation in abdominal CT of colorectal liver

Uncertainty-Aware Calibrated Clinical Text Classification with Large Language Models

arXiv:2509.19375v2 Announce Type: replace-cross Abstract: Large language models are increasingly used for clinical text classification, where overconfident misclassifications can directly affect patie

Agents

CanvasAnneal: Curriculum Reinforcement Learning for Diffusion Language Models

arXiv:2609.13060v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) offer promising parallel generation capabilities but lag behind autoregressive models in complex reasoning and tool-use

agentsarxiv-cs-lg

14 Sept 2026

For all the focus on hard math, we should also have a bank of historical mysteries and cyphers that we can throw models at. I know a few his…

model-releasesethan-mollick--x

For all the focus on hard math, we should also have a bank of historical mysteries and cyphers that we can throw models at. I know a few historians (like https://generativehistory.substack.com/) that

14 Sept 2026

Parallel Training Using a CNN-DNN Architecture for Accelerated Development of Diagnostic Models

arXiv:2609.12902v1 Announce Type: new Abstract: Artificial intelligence has shown promise in assisting radiologists in imaging-based diagnosis across a wide range of diseases. Efficient training of la

researcharxiv-cs-cv

14 Sept 2026

Local Ai

Many concerns this weekend about slowing down AI, some targeting open models. We need to be responsible. But we can't let this slow down, or…

Many concerns this weekend about slowing down AI, some targeting open models. We need to be responsible. But we can't let this slow down, or worse, prohibit open models. It's the wrong risk. Open mode

local-aiollama--x

13 Sept 2026

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

arXiv:2609.11872v1 Announce Type: cross Abstract: Continuous glucose monitoring (CGM) provides high-frequency measurements of glucose dynamics and enables short-term glucose forecasting for diabetes m

Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis

arXiv:2506.00849v2 Announce Type: replace Abstract: Despite the empirical success of Diffusion Models (DMs) and Variational Autoencoders (VAEs), their generalization performance remains theoretically

MindTopo: Can Foundation Models Reason in Topological Space?

arXiv:2609.11900v1 Announce Type: cross Abstract: Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant un

Smoothing the Score Function to Enhance Generalization in Diffusion Models

arXiv:2601.19285v3 Announce Type: replace Abstract: Diffusion models achieve remarkable generation quality, yet face a fundamental challenge known as memorization, where generated samples can replicat

Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation

arXiv:2601.15645v2 Announce Type: replace Abstract: Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing stu

Tutorials

Arlequin AI raises €28M to build novel AI models that learn complex relationships at scale

Paris-based Arlequin AI SAS today announced it raised €28 million, about $32 million, in new funding to accelerate development of a new AI model architecture based on a different type of network that

tutorialssiliconangle

From Fixed Keys to Readable Schemas: Small Language Models for Vehicle Agent Function Calls

arXiv:2609.09476v1 Announce Type: cross Abstract: In-vehicle assistants must translate natural-language requests into accurate vehicle function calls under strict memory and latency constraints, makin

In-Place Instruction Following in Diffusion Language Models

arXiv:2609.07160v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) generate text via bidirectional iterative denoising, naturally supporting user-specified constraints anchored

Interpreting Object-Dependent Concept Brittleness in Text-to-Image Diffusion Models

arXiv:2609.09909v1 Announce Type: new Abstract: Although text-to-image diffusion models generally exhibit strong prompt-following ability, we identify a persistent and previously underexplored failure

researcharxiv-cs-cv

Limits of Reliability and Scaling in Language Models

arXiv:2607.14112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained and evaluated as though perfect reliability is achievable for any task given sufficient scale. We sho

researcharxiv-cs-ai

Test-time Prompt Refinement for Text-to-Image Models

arXiv:2507.22076v2 Announce Type: replace Abstract: Text-to-image (T2I) generation models have made significant strides but still struggle with prompt sensitivity: even minor changes in prompt wording

Safety

An overview of 3D Vision-Language Models

arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and

safetyarxiv-cs-cv

Counterfactual Tests for Measuring Chain-of-Thought Faithfulness in Visual Language Models

arXiv:2609.06704v1 Announce Type: new Abstract: Chain-of-thought (CoT) may often look plausible, yet it may not faithfully reflect the model's decision-making process. While methods for measuring the

Safety

DIVA: Exploiting Cross-Step Conditional Propagation for Visual Jailbreaks in Discrete Diffusion Vision-Language Models

arXiv:2609.05525v1 Announce Type: new Abstract: Large vision-language models (VLMs) are increasingly deployed in safety-critical settings, yet existing visual jailbreak research has focused almost exc

safetyarxiv-cs-cv

MpSub: A Momentum p-Dimensional Subspace Trust-Region Method for Derivative-Free Fine-Tuning of Large Language Models

arXiv:2609.07666v1 Announce Type: new Abstract: Full-parameter fine-tuning of large language models has substantial memory costs because backpropagation stores activations and gradients. Zeroth-order

NoLoCo: No-all-reduce Low Communication Training Method for Large Models

arXiv:2506.10911v2 Announce Type: replace Abstract: Training large language models is generally done on clusters containing thousands of accelerators, communicating over a high-bandwidth interconnect.

Revisiting Spectral Representations in Generative Diffusion Models

arXiv:2609.08253v1 Announce Type: new Abstract: Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposing representation alignment on the hidden s

The EM-algorithm and the Method of Moments in Softmax Mixture Models

arXiv:2409.09903v3 Announce Type: replace-cross Abstract: Softmax Mixture Models (SMMs) are discrete K-component mixture models for the probabilities of selecting one of p candidate feature vectors X_

Locus - A MacOS tool for Ollama and other local models

Hey so a few months ago I got into local LLMs and didn’t really like the tools out there at the time, so I decided to build my own version of a Claude/Codex GUI for local models. I’ve been working on

model-releasesr-ollama

8 Sept 2026

Mistral raised a €3B Series D led by Samsung at a €21B valuation, up from €11.7B a year ago, as it expands into data centers beyond developing AI models (Adam Satariano/New York Times)

Adam Satariano / New York Times: Mistral raised a €3B Series D led by Samsung at a €21B valuation, up from €11.7B a year ago, as it expands into data centers beyond developing AI models — Mistral is t

model-releasestechmeme

8 Sept 2026

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

arXiv:2609.04720v1 Announce Type: cross Abstract: Vision-language models (VLMs) are expected to respond helpfully to appropriate requests while withholding compliance with requests that are incorrect,

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

arXiv:2609.05324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchma

Same Trajectory, Contradictory Rewards (ROBORMBENCH): Paraphrase Fragility in Vision Language Reward Models

arXiv:2609.05401v1 Announce Type: cross Abstract: Vision-language models are increasingly used as reward functions for robotic learning, but this role requires paraphrase invariance: the same trajecto

When Do Internal Probes Beat Reading the Answer? Miscalibrated Readouts and Behavior-Concealed Knowledge in Language Models

arXiv:2609.04582v1 Announce Type: cross Abstract: A 0.6B language model, asked to verify 1,200 logical conclusions (half valid, half corrupted by a single semantic edit), answers YES every time. Judge

ALRA: Adaptive Local Relational Alignment for Logit-Based Pre-training Distillation of Autoregressive Language Models

arXiv:2609.03355v1 Announce Type: cross Abstract: Logit-based knowledge distillation for autoregressive language models usually aligns teacher and student next-token distributions over the entire voca

Causal Foundation Models

arXiv:2609.03003v1 Announce Type: new Abstract: Causal inference is the practice of estimating the effect of a treatment or intervention from data. It traditionally requires a bespoke pipeline for eve

Evaluating Criterion-Conditioned Behaviour of Large Language Models in Content Moderation

arXiv:2609.03814v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance on standard content moderation benchmarks. However, these benchmarks often aggregate multipl

Local Ai

WeatherNext 3: Increasing resolution and performance of global weather models with raw observations

arXiv:2609.03582v1 Announce Type: new Abstract: State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: thei

local-aiarxiv-cs-lg