Search: “models”

Overstating Attitudes, Ignoring Networks: LLM Biases in Simulating Misinformation Susceptibility

arXiv:2602.04674v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reprodu

researcharxiv-cs-ai

Research

PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images

DGX agent

arXiv:2511.20068v2 Announce Type: replace Abstract: Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large l

researcharxiv-cs-cv

13 Apr 2026

Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization

arXiv:2602.02188v2 Announce Type: replace Abstract: While large language models (LLMs) have shown strong performance in math and logic reasoning, their ability to handle combinatorial optimization (CO

SAGE: A Service Agent Graph-guided Evaluation Benchmark

arXiv:2604.09285v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has catalyzed automation in customer service, yet benchmarking their performance remains challenging. Ex

Skill-Conditioned Visual Geolocation for Vision-Language

arXiv:2604.09025v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown a promising ability in image geolocation, but they still lack structured geographic reasoning and the capacit

So the concern over Mythos and cybersecurity seems warranted.

model-releasesethan-mollick--x

So the concern over Mythos and cybersecurity seems warranted. We conducted cyber evaluations of Claude Mythos Preview and found that it is the first model to complete an AISI cyber range end-to-end. 🧵

SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions

arXiv:2604.08477v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has significantly improved large language model (LLM) reasoning in formal domains such as mathem

researcharxiv-cs-cl

Turning Anime into Real and testing Klein9b vs Qwen Edit 2511 (Workflow Included)

model-releasesr-stablediffusion

This r/StableDiffusion post showcases a workflow for converting anime-style images into photorealistic outputs, directly comparing two AI image editing models: Klein 9B and Qwen Image Edit 2511. Qwen

UIPress: Bringing Optical Token Compression to UI-to-Code Generation

arXiv:2604.09442v1 Announce Type: new Abstract: UI-to-Code generation requires vision-language models (VLMs) to produce thousands of tokens of structured HTML/CSS from a single screenshot, making visu

researcharxiv-cs-cl

Tutorials

You Can't Fight in Here! This is BBS!

arXiv:2604.09501v1 Announce Type: new Abstract: Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models

tutorialsarxiv-cs-cl

Agents

Amazing article. If you own the harness you own your memories. Else you get locked into an API model which keeps memory behind APIs and you …

Harrison Chase, co-founder of LangChain, shared or engaged with commentary emphasizing the importance of owning your own memory harness in AI applications rather than relying on third-party API-based

agentsharrison-chase--x

12 Apr 2026

Tools

MiniMax M2.7 is now on Together AI. Trained by letting it run its own RL loop, resulting in the highest open-source score on MLE Bench Lite.

MiniMax M2.7 is now available on Together AI, offering a powerful open-source model trained using a self-directed reinforcement learning loop. This training methodology enabled the model to achieve th

toolstogether-ai--x

12 Apr 2026

Qwen 2511 fp8 mixed taking 30–40s per image edit — which GGUF should I use?

model-releasesr-stablediffusion

This r/StableDiffusion thread addresses performance issues with the Qwen-Image-Edit-2511 FP8 mixed model in ComfyUI, where users experience slow image edit times of 30–40 seconds per step (or overall)

12 Apr 2026

Local Ai

My 2026 Ollama Setup Guide: What Actually Works Best for Daily Use on Consumer Hardware

This r/ollama community post is a practitioner's guide sharing personal, real-world experience running Ollama on everyday consumer hardware in 2026, covering which models, quantization settings, and c

local-air-ollama

11 Apr 2026

We've been tricked, again. Many of the thousands of bugs and vulnerabilities Mythos found are in older software are impossible to exploit. A…

model-releasesyann-lecun--x

We've been tricked, again. Many of the thousands of bugs and vulnerabilities Mythos found are in older software are impossible to exploit. And the severe zero-day reports rely on just 198 manual revie

11 Apr 2026

A Parameter-Efficient Transfer Learning Approach through Multitask Prompt Distillation and Decomposition for Clinical NLP

arXiv:2604.06650v1 Announce Type: cross Abstract: Existing prompt-based fine-tuning methods typically learn task-specific prompts independently, imposing significant computing and storage overhead at

A playable, digital piano built with Gemma 4 E2B (2B). https://x.com/0xCVYH/status/2039929097141318129?s=20

model-releasesgoogle-ai--x

A playable, digital piano built with Gemma 4 E2B (2B). https://x.com/0xCVYH/status/2039929097141318129?s=20 Google lancou 'Agent Skills' junto com o Gemma 4 Um app Android onde voce importa skills e o

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s

Local Ai

Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test

arXiv:2506.06975v5 Announce Type: replace-cross Abstract: As API access becomes a primary interface to large language models (LLMs), users often interact with black-box systems that offer little trans

local-aiarxiv-cs-cl

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing

model-releasesarxiv-cs-lg

arXiv:2510.03046v2 Announce Type: replace Abstract: Machine learning potentials (MLPs) have become essential for large-scale atomistic simulations, enabling ab initio-level accuracy with computational

Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

arXiv:2604.06173v1 Announce Type: cross Abstract: Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory do

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts

arXiv:2604.08519v1 Announce Type: new Abstract: Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on kno

researcharxiv-cs-cl

Create Expert Content: Local Testing of a Multi-Agent System with Memory

model-releasesgoogle-cloud-ai

In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by

CycleChart: A Unified Consistency-Based Learning Framework for Bidirectional Chart Understanding and Generation

arXiv:2512.19173v2 Announce Type: replace Abstract: Current chart-related tasks, such as chart generation (NL2Chart), chart schema parsing, chart data parsing, and chart question answering (ChartQA),

Distilling Specialized Orders for Visual Generation

arXiv:2504.17069v2 Announce Type: replace Abstract: Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Ty

researcharxiv-cs-cv

Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents

arXiv:2604.08369v1 Announce Type: cross Abstract: Inference-time compute scaling has emerged as a powerful technique for improving the reliability of large language model (LLM) agents, but existing me

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2410.17473v2 Announce Type: replace Abstract: In reinforcement learning (RL), temporal difference (TD) error is known to be related to the firing rate of dopamine neurons. It has been observed t

Dual-level Modality Debiasing Learning for Unsupervised Visible-Infrared Person Re-Identification

arXiv:2512.03745v2 Announce Type: replace Abstract: Two-stage learning pipeline has achieved promising results in unsupervised visible-infrared person re-identification (USL-VI-ReID). It first perform

ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions

arXiv:2604.07772v1 Announce Type: new Abstract: Open-world video anomaly detection (OWVAD) aims to detect and explain abnormal events under different anomaly definitions, which is important for applic

Evaluating LLM-Based 0-to-1 Software Generation in End-to-End CLI Tool Scenarios

arXiv:2604.06742v1 Announce Type: cross Abstract: Large Language Models (LLMs) are driving a shift towards intent-driven development, where agents build complete software from scratch. However, existi

Tutorials

Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration

arXiv:2603.16570v2 Announce Type: replace Abstract: Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models

tutorialsarxiv-cs-cv

FLeX: Fourier-based Low-rank EXpansion for multilingual transfer

arXiv:2604.06253v1 Announce Type: cross Abstract: Cross-lingual code generation is critical in enterprise environments where multiple programming languages coexist. However, fine-tuning large language

Safety

From Ground Truth to Measurement: A Statistical Framework for Human Labeling

arXiv:2604.07591v1 Announce Type: cross Abstract: Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human

safetyarxiv-cs-cl

Safety

FVD: Inference-Time Alignment of Diffusion Models via Fleming-Viot Resampling

arXiv:2604.06779v1 Announce Type: new Abstract: We introduce Fleming-Viot Diffusion (FVD), an inference-time alignment method that resolves the diversity collapse commonly observed in Sequential Monte

safetyarxiv-cs-ai

HiCI: Hierarchical Construction-Integration for Long-Context Attention

arXiv:2603.20843v2 Announce Type: replace Abstract: Long-context language modeling is commonly framed as a scalability challenge of token-level attention, yet local-to-global information structuring r

Tutorials

How to sketch a learning algorithm

arXiv:2604.07328v1 Announce Type: new Abstract: How does the choice of training data influence an AI model? This question is of central importance to interpretability, privacy, and basic science. At i

tutorialsarxiv-cs-lg

In-Context Decision Making for Optimizing Complex AutoML Pipelines

arXiv:2508.13657v2 Announce Type: replace-cross Abstract: Combined Algorithm Selection and Hyperparameter Optimization (CASH) has been fundamental to traditional AutoML systems. However, with the adva

KEO: Knowledge Extraction on OMIn via Knowledge Graphs and RAG for Safety-Critical Aviation Maintenance

arXiv:2510.05524v2 Announce Type: replace Abstract: We present Knowledge Extraction on OMIn (KEO), a domain-specific knowledge extraction and reasoning framework with large language models (LLMs) in s

Mitigating Spurious Background Bias in Multimedia Recognition with Disentangled Concept Bottlenecks

arXiv:2510.15770v3 Announce Type: replace Abstract: Concept Bottleneck Models (CBMs) enhance interpretability by predicting human-understandable concepts as intermediate representations. However, exis

Noise Immunity in In-Context Tabular Learning: An Empirical Robustness Analysis of TabPFN's Attention Mechanisms

arXiv:2604.04868v2 Announce Type: replace-cross Abstract: Tabular foundation models (TFMs) such as TabPFN (Tabular Prior-Data Fitted Network) are designed to generalize across heterogeneous tabular da

On the Step Length Confounding in LLM Reasoning Data Selection

arXiv:2604.06834v1 Announce Type: cross Abstract: Large reasoning models have recently demonstrated strong performance on complex tasks that require long chain-of-thought reasoning, through supervised

researcharxiv-cs-ai

Safety

Quality-preserving Model for Electronics Production Quality Tests Reduction

arXiv:2604.06451v1 Announce Type: new Abstract: Manufacturing test flows in high-volume electronics production are typically fixed during product development and executed unchanged on every unit, even

safetyarxiv-cs-lg

Qwen 3.6 Plus on AI Gateway

model-releasesvercel-blog

Alibaba's Qwen 3.6 Plus is now available on Vercel's AI Gateway, accessible via a unified API with no additional provider accounts required. Compared to Qwen 3.5 Plus, this model adds stronger age...

Local Ai

qwen3.5 no se instala

Users in the r/ollama community reported that Qwen3.5 models fail to install or load in Ollama, with common errors including 'Error: 500 Internal Server Error: unable to load model' even after a ...

local-air-ollama

Agents

Scaling-Aware Data Selection for End-to-End Autonomous Driving Systems

arXiv:2604.08366v1 Announce Type: cross Abstract: Large-scale deep learning models for physical AI applications depend on diverse training data collection efforts. These models and correspondingly, th

agentsarxiv-cs-cv

Sell More, Play Less: Benchmarking LLM Realistic Selling Skill

arXiv:2604.07054v2 Announce Type: replace Abstract: Sales dialogues require multi-turn, goal-directed persuasion under asymmetric incentives, which makes them a challenging setting for large language

SpatialMosaic: A Multiview VLM Dataset for Partial Visibility

arXiv:2512.23365v3 Announce Type: replace Abstract: The rapid progress of Multimodal Large Language Models (MLLMs) has unlocked the potential for enhanced 3D scene understanding and spatial reasoning.

Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation

arXiv:2604.07028v1 Announce Type: cross Abstract: Strategic interaction in adversarial domains such as law, diplomacy, and negotiation is mediated by language, yet most game-theoretic models abstract