Search: “models”

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users

arXiv:2603.16120v2 Announce Type: replace Abstract: Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queri

Model Releases

Latent Preference Modeling for Cross-Session Personalized Tool Calling

DGX agent

arXiv:2604.17886v1 Announce Type: new Abstract: Users often omit essential details in their requests to LLM-based agents, resulting in under-specified inputs for tool use. This poses a fundamental cha

model-releasesarxiv-cs-cl

21 Apr 2026

Long-Text-to-Image Generation via Compositional Prompt Decomposition

arXiv:2604.18258v1 Announce Type: new Abstract: While modern text-to-image (T2I) models excel at generating images from intricate prompts, they struggle to capture the key details when the inputs are

LoReC: Rethinking Large Language Models for Graph Data Analysis

arXiv:2604.17897v1 Announce Type: new Abstract: The advent of Large Language Models (LLMs) has fundamentally reshaped the way we interact with graphs, giving rise to a new paradigm called GraphLLM. As

Modeling, Control and Self-sensing of Dielectric Elastomer Soft Actuators: A Review

arXiv:2604.17199v1 Announce Type: new Abstract: Dielectric elastomer actuators (DEAs) have garnered extensive attention especially in soft robotic applications over the past few decades owing to the a

researcharxiv-cs-ro

Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis

arXiv:2604.17713v1 Announce Type: new Abstract: Resting-state functional magnetic resonance imaging (fMRI) has emerged as a cornerstone for psychiatric diagnosis, yet most approaches rely on pairwise

Modelling Gas-Phase Reaction Kinetics with Guided Particle Diffusion Sampling

arXiv:2604.16461v1 Announce Type: cross Abstract: Physics-guided sampling with diffusion priors has recently shown strong performance in solving complex systems of partial differential equations (PDEs

Operationalizing Fairness in Text-to-Image Models: A Survey of Bias, Fairness Audits and Mitigation Strategies

arXiv:2604.16516v1 Announce Type: new Abstract: Text-to-Image (T2I) generation models have been widely adopted across various industries, yet are criticized for frequently exhibiting societal stereoty

safetyarxiv-cs-cv

PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection

arXiv:2505.20211v3 Announce Type: replace Abstract: Fine-tuning large foundation models is essential for building expert models tailored to specialized tasks and domains, but fully updating billions o

Safer Trajectory Planning with CBF-guided Diffusion Model for Unmanned Aerial Vehicles

arXiv:2604.17527v1 Announce Type: new Abstract: Safe and agile trajectory planning is essential for autonomous systems, especially during complex aerobatic maneuvers. Motivated by the recent success o

safetyarxiv-cs-ro

Shifting the Gradient: Understanding How Defensive Training Methods Protect Language Model Integrity

arXiv:2604.16423v1 Announce Type: new Abstract: Defensive training methods such as positive preventative steering (PPS) and inoculation prompting (IP) offer surprising results through seemingly simila

applicationsarxiv-cs-lg

SinkRouter: Sink-Aware Routing for Efficient Long-Context Decoding in Large Language and Multimodal Models

arXiv:2604.16883v1 Announce Type: new Abstract: In long-context decoding for LLMs and LMMs, attention becomes increasingly memory-bound because each decoding step must load a large amount of KV-cache

Spotlights and Blindspots: Evaluation Machine-Generated Text Detection

arXiv:2604.16607v1 Announce Type: new Abstract: With the rise of generative language models, machine-generated text detection has become a critical challenge. A wide variety of models is available, bu

researcharxiv-cs-cl

Target Parameterization in Diffusion Models for Nonlinear Spatiotemporal System Identification

arXiv:2604.17566v1 Announce Type: cross Abstract: Machine learning is becoming increasingly important for nonlinear system identification, including dynamical systems with spatially distributed output

Tutorials

This is what I’ve been cooking in the past 4 months . GPT Image 2 is over a massive 240 elo jump over the second place model, marking the bi…

tutorialsjeremy-howard--x

This is what I’ve been cooking in the past 4 months . GPT Image 2 is over a massive 240 elo jump over the second place model, marking the biggest jump bigger than the rest of the leaderboard combined

Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data

arXiv:2604.18493v1 Announce Type: new Abstract: Reinforcement Learning (RL) enhances LLM reasoning, yet a paradox emerges as models scale: strong base models saturate standard benchmarks (e.g., MATH),

Towards Real-Time ECG and EMG Modeling on mu NPUs

arXiv:2604.18067v1 Announce Type: new Abstract: The miniaturisation of neural processing units (NPUs) and other low-power accelerators has enabled their integration into microcontroller-scale wearable

Arrow 1.1, the latest model from @QuiverAI, is now supported in ComfyUI as a Partner Node, offering scalable, editable SVG output directly w…

Arrow 1.1, the latest model from @QuiverAI, is now supported in ComfyUI as a Partner Node, offering scalable, editable SVG output directly within ComfyUI. What creators use it for: - Logos & wordmarks

applicationscomfyui--x

Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards

arXiv:2510.07774v3 Announce Type: replace Abstract: In this paper, we observe that current models are susceptible to reward hacking, leading to a substantial overestimation of a model's reasoning abil

researcharxiv-cs-cl

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

arXiv:2512.23421v3 Announce Type: replace Abstract: World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the rea

Early Detection of Acute Myeloid Leukemia (AML) Using YOLOv12 Deep Learning Model

arXiv:2604.16082v1 Announce Type: cross Abstract: Acute Myeloid Leukemia (AML) is one of the most life-threatening type of blood cancers, and its accurate classification is considered and remains a ch

researcharxiv-cs-ai

Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image Models

arXiv:2504.01137v3 Announce Type: replace Abstract: Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the t

safetyarxiv-cs-cl

Import AI 454: Automating alignment research; safety study of a Chinese model; HiFloat4

This newsletter covers three main topics: advances in automating alignment research to improve AI safety processes, a safety evaluation study of a Chinese AI model, and technical details about HiFloat

safetyimport-ai

Prototype-Grounded Concept Models for Verifiable Concept Alignment

arXiv:2604.16076v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) aim to improve interpretability in Deep Learning by structuring predictions through human-understandable concepts, bu

safetyarxiv-cs-ai

The Spectral Geometry of Thought: Phase Transitions, Instruction Reversal, Token-Level Dynamics, and Perfect Correctness Prediction in How Transformers Reason

arXiv:2604.15350v1 Announce Type: new Abstract: We discover that large language models exhibit spectral phase transitions in their hidden activation spaces when engaging in reasoning versus factual re

Local Ai

Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization

arXiv:2604.16248v1 Announce Type: new Abstract: Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent

local-aiarxiv-cs-cv

Hardware

Sources: Google is in talks with Marvell Technology to develop a memory processing unit that works alongside TPUs, and a new TPU for running AI models (Qianer Liu/The Information)

Qianer Liu / The Information: Sources: Google is in talks with Marvell Technology to develop a memory processing unit that works alongside TPUs, and a new TPU for running AI models — Google is in talk

hardwaretechmeme

19 Apr 2026

Tools

A new programming model for durable execution

This article from Vercel presents a new programming model designed to enable durable execution of applications, likely addressing how to handle long-running tasks, failures, and retries in serverless

toolsvercel-blog

Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models

arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow

researcharxiv-cs-cl

Hardware

Bit-Accurate Modeling of GPU Matrix Multiply-Accumulate Units: Demystifying Numerical Discrepancy and Accuracy

arXiv:2511.10909v2 Announce Type: replace-cross Abstract: Modern AI accelerators rely on matrix multiply-accumulate units (MMAUs), such as NVIDIA Tensor Cores and AMD Matrix Cores, to accelerate deep

hardwarearxiv-cs-lg

Blinded Multi-Rater Comparative Evaluation of a Large Language Model and Clinician-Authored Responses in CGM-Informed Diabetes Counseling

arXiv:2604.15124v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) is central to diabetes care, but explaining CGM patterns clearly and empathetically remains time-intensive. Evidence

safetyarxiv-cs-cl

Can Large Language Models Detect Methodological Flaws? Evidence from Gesture Recognition for UAV-Based Rescue Operation Based on Deep Learning

arXiv:2604.14161v1 Announce Type: new Abstract: Reliable evaluation is essential in machine learning research, yet methodological flaws-particularly data leakage-continue to undermine the validity of

applicationsarxiv-cs-cl

Frame forecasting in cine MRI using the PCA respiratory motion model: comparing recurrent neural networks trained online and transformers

arXiv:2410.05882v3 Announce Type: replace-cross Abstract: Respiratory motion complicates accurate irradiation of thoraco-abdominal tumors during radiotherapy, as treatment-system latency entails targe

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions

arXiv:2502.16761v2 Announce Type: replace Abstract: Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stage

applicationsarxiv-cs-cl

MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models

arXiv:2604.14582v1 Announce Type: new Abstract: High-resolution (HR) land-cover mapping is often constrained by the high cost of dense HR annotations. We revisit this problem from the perspective of m

researcharxiv-cs-cv

MemGround: Long-Term Memory Evaluation Kit for Large Language Models in Gamified Scenarios

arXiv:2604.14158v1 Announce Type: new Abstract: Current evaluations of long-term memory in LLMs are fundamentally static. By fixating on simple retrieval and short-context inference, they neglect the

Mitigating LLM biases toward spurious social contexts using direct preference optimization

arXiv:2604.02585v2 Announce Type: replace-cross Abstract: LLMs are increasingly used for high-stakes decision-making, yet their sensitivity to spurious contextual information can introduce harmful bia

Model-Based Reinforcement Learning under Random Observation Delays

arXiv:2509.20869v2 Announce Type: replace Abstract: Delays frequently occur in real-world environments, yet standard reinforcement learning (RL) algorithms often assume instantaneous perception of the

applicationsarxiv-cs-lg

Hardware

Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3

arXiv:2603.27844v2 Announce Type: replace Abstract: Majority voting over multiple LLM attempts improves mathematical reasoning, but correlated errors limit the effective sample size. A natural fix is

hardwarearxiv-cs-cl

SegviGen: Repurposing 3D Generative Model for Part Segmentation

arXiv:2603.16869v2 Announce Type: replace Abstract: We introduce SegviGen, a framework that repurposes native 3D generative models for 3D part segmentation. Existing pipelines either lift strong 2D pr

researcharxiv-cs-cv

Local Ai

Atelier: a canvas for thinking and making with local models.

local-air-stablediffusion

Atelier is a canvas-like system that leverages generative image and video models to blend spaces for thinking and creation, where both references and generated assets co-exist in one unified workspace

BenGER: A Collaborative Web Platform for End-to-End Benchmarking of German Legal Tasks

arXiv:2604.13583v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for legal reasoning requires workflows that span task design, expert annotation, model execution, and metric-bas

Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Glucose Forecasting

arXiv:2411.10703v3 Announce Type: replace Abstract: The availability of continuous glucose monitors as over-the-counter commodities have created a unique opportunity to monitor a person's blood glucos

applicationsarxiv-cs-lg

Industry

Memo: the White House notified Cabinet departments that OMB is setting up protections that would allow their agencies to begin using Anthropic's Mythos model (Bloomberg)

Bloomberg: Memo: the White House notified Cabinet departments that OMB is setting up protections that would allow their agencies to begin using Anthropic's Mythos model — The US government is preparin

industrytechmeme

Agents

Numerical Instability and Chaos: Quantifying the Unpredictability of Large Language Models

arXiv:2604.13206v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into agentic workflows, their unpredictability stemming from numerical instability has eme

agentsarxiv-cs-lg

PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling

arXiv:2604.13986v1 Announce Type: new Abstract: Predicting the effects of perturbations in-silico on cell state can identify drivers of cell behavior at scale and accelerate drug discovery. However, m

Qwen3.6-35B-A3B on my laptop drew me a better pelican than Claude Opus 4.7

model-releasessimon-willison

For anyone who has been (inadvisably) taking my pelican riding a bicycle benchmark seriously as a robust way to test models, here are pelicans from this morning's two big model releases - Qwen3.6-35B-

ROSE: Retrieval-Oriented Segmentation Enhancement

arXiv:2604.14147v1 Announce Type: new Abstract: Existing segmentation models based on multimodal large language models (MLLMs), such as LISA, often struggle with novel or emerging entities due to thei