Search: “models”

When May a Model Replace the Experiment? Audits, Licenses, and the Price of Trust in Surrogate-Driven Design

arXiv:2608.01378v1 Announce Type: new Abstract: Design campaigns in chemistry, materials science, and machine learning share a bottleneck: determining how good a candidate truly is requires an expensi

safetyarxiv-cs-lg

4 Aug 2026

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Tutorials

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

DGX agent

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

tutorialsarxiv-cs-ai

3 Aug 2026

KAT Coder 2.5 dev: Do yourself a favor and try it!

It is so good! I don't know why there aren't more people talking about it. Fewer tokens, faster and more accurate than Qwen 3.6 35b a3b. On my setup it's nearly as good as 27b, but 5x faster. And it c

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und

ReLoop-UME: Recurrent Depth with Learnable Retrieval Registers for Universal Multimodal Embedding

model-releasesarxiv-cs-cv

arXiv:2607.28751v1 Announce Type: new Abstract: Universal multimodal embedding (UME) maps heterogeneous multimodal inputs into a shared embedding space. Existing UME models either form embeddings thro

The Grokked Illusion: True Equilibrium Mitigates Catastrophic Forgetting

arXiv:2607.29503v1 Announce Type: new Abstract: While neural networks are typically evaluated by their training and test performance, these metrics do not reveal how robust a learned representation is

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

researcharxiv-cs-cl

Tokenizer-Agnostic Engram Module

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

DeepSeek-V4-Flash 284B on 5.3GB of memory

Following up on my Qwen 3.6 port, I wanted to keep adding models and ended up fixing a bunch of things along the way, so it's its own engine now: Mference. Same core idea from TurboFieldfare, MoE mode

2 Aug 2026

How well do multiple GPUs scale for LLM inference? (Trying to understand the basics)

Hi everyone, I’m fairly new to the multi-GPU side of local LLMs and I’m trying to understand how inference actually scales across multiple GPUs. Suppose I have a model running on a single GPU and then

2 Aug 2026

Real-world reality check on Qwen for autonomous coding agents

TLDR below 👇🏼 I’ve seen a lot of hype around Qwen 3.6 35B and 3.5 120B lately, especially regarding coding and tool-use capabilities. On this subreddit it is the defacto recommended model for everyone

2 Aug 2026

Tutorials

There's no 'one weird trick” for prompting Krea 2 art styles—just many guidelines [WF included]

tutorialsr-stablediffusion

TLDR: There is no one prompting trick that will result in Krea 2 Turbo giving you exactly the style you want and across the whole image. Instead, if you are trying to achieve styles without the use of

1 Aug 2026

Industry

AI-native software development requires a new engineering model

Artificial intelligence has quickly become a standard part of modern software development. Coding assistants, code completion tools and AI-powered integrated development environments are now widely av

industrysiliconangle

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil

Hardware

Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference

The article shows that dense‑attention performance in long‑context inference is governed by group size (query heads per KV head), head dimension, and sequence length, with prefill being compute‑bound

hardwarenvidia-developer

IGME: Efficient Chained Method Ensemble for Transferable Semantic Segmentation Attacks

arXiv:2607.27465v1 Announce Type: new Abstract: Semantic segmentation models are vulnerable to transferable adversarial perturbations, yet evaluating transfer attacks on dense prediction models can be

researcharxiv-cs-cv

Latent-Kernel Discrete Flow Maps for Few-Step Generation

arXiv:2607.27529v1 Announce Type: new Abstract: Discrete diffusion and flow-matching models denoise a sequence over many steps, but to keep each step cheap, they factorize the transition across positi

researcharxiv-cs-lg

MORFES: A Benchmark for Productive Inflectional Competence in Modern Greek

arXiv:2607.28274v1 Announce Type: new Abstract: Modern Greek is a richly inflected language, yet the language models built for it are evaluated mainly on factual knowledge, and no benchmark is dedicat

Applications

Scalable Drift Monitoring in Medical Imaging AI

arXiv:2410.13174v3 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model

applicationsarxiv-cs-cv

Sympathetic Framing: Evaluating AI Alignment across Sociodemographic Groups

arXiv:2607.27232v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly shaping how we consume information and form our worldview. This raises concerns beyond bias in AI: do LLMs

Zero-Shot Face-to-Speech Synthesis via Latent Space Adaptation of a Style-Diffusion TTS Model

arXiv:2607.26742v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) clones a voice from a short audio prompt, but this reliance on reference audio is a barrier when only visual informatio

researcharxiv-cs-ai

Benchmarked: MindControl for Llama.cpp

I recently shared the original MindControl PoC (and on github) - sampler-level guided reasoning budgets for llama.cpp, nudging the model with self-aware statements about its own thinking budget instea

CheckVLA: Execution-Time Verification with Action-Conditioned World Model for Long-Horizon Mobile Manipulation

arXiv:2607.26789v1 Announce Type: new Abstract: Vision-language-action (VLA) policies commonly execute long-horizon mobile manipulation through open-loop action chunks, issuing multiple actions withou

safetyarxiv-cs-ro

ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information

arXiv:2106.16038v3 Announce Type: replace Abstract: Recent pretraining models in Chinese neglect two important aspects specific to the Chinese language: glyph and pinyin, which carry significant synta

researcharxiv-cs-cl

GEqTrain: A Configuration-Driven Framework for Retargeting Equivariant Graph Neural Networks Across 3D Scientific Tasks

arXiv:2607.19083v2 Announce Type: replace Abstract: Equivariant graph neural networks provide a powerful modeling language for three-dimensional scientific data, but their reuse is often limited by im

How Kimi K3 Engineered Its Way to the Frontier [R]

model-releasesr-machinelearning

Kimi K3 by Moonshot reached the frontier as an open-weight model. Artificial Analysis ranks it fourth of 580 models, behind only Claude Opus 5, Fable 5, and GPT-5.6 Sol. Moonshot released more than th

Nanbeige4.2-3B: I'm not impressed

I've tested Nanbeige-4.2-3B. On paper, the benchmarks promise it blows away Qwen3.5-9B and Gemma4-12B. My goal was to have something very light and fast to replace Qwen3.6-35B (or finetunes thereof) f

Local Ai

Origins and mitigation of double descent in reduced order modeling

arXiv:2607.26414v1 Announce Type: cross Abstract: Latent low-dimensional structure in datasets of natural and engineered systems enables their sparse sensing, or full-state reconstruction from histori

local-aiarxiv-cs-lg

Post-Training at the Edge of Detectability: A Game-Theoretic Approach to Fine-Tuning

arXiv:2607.26358v1 Announce Type: new Abstract: Reinforcement learning (RL) fine-tuning is widely used in language model training to improve model performance on a target task while limiting drift fro

Prosody-driven Jailbreaks in Audio LLMs: A Controlled Study and Mechanistic Analysis

arXiv:2607.26541v1 Announce Type: cross Abstract: Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains uncle

SERPO: Self-Evolving Rubric Policy Optimization for Open-Ended Test-Time Reinforcement Learning

arXiv:2607.26873v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) enables language models to self-evolve at inference time without labeled feedback. Existing methods rely on answ

DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space

arXiv:2607.25675v1 Announce Type: new Abstract: Text-space optimization adapts large language models (LLMs) by editing external natural-language artifacts rather than model weights, so the optimized a

Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Cases

arXiv:2607.25933v1 Announce Type: cross Abstract: Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practic

Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales

arXiv:2607.25364v1 Announce Type: new Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection

safetyarxiv-cs-ai

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms

arXiv:2607.24960v1 Announce Type: cross Abstract: We present a neural network surrogate model that emulates the NRSur7dq4 gravitational waveform model for precessing binary black hole mergers. The sur

Finding Optimal Cost-Bounded Plan Reductions: Refined Model

arXiv:2607.25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original act

researcharxiv-cs-ai

Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels

arXiv:2607.24762v1 Announce Type: new Abstract: Machine learning models are increasingly embedded in everyday software, and most of their runtime is spent in a small set of compute kernels such as mat

Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation

arXiv:2607.25956v1 Announce Type: new Abstract: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matche

safetyarxiv-cs-ai

Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model

arXiv:2510.22863v2 Announce Type: replace-cross Abstract: Reliable long-term forecasting of PM2.5 concentrations is critical for public health early-warning systems, yet existing deep learning approac

researcharxiv-cs-ai

RIDGE: An Autonomous Framework for Validation and Method Discovery in LLM-Generated Option Pricing

arXiv:2607.25199v1 Announce Type: cross Abstract: Automated code generation is becoming an important tool in quantitative finance, where large language models can generate option pricing implementatio

RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement

arXiv:2607.25886v1 Announce Type: cross Abstract: Recursive self-improvement requires turning evidence of model failures into better models. Data-centric post-training research entails diagnosing capa

Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions

arXiv:2607.25026v1 Announce Type: cross Abstract: In this work, we present a simulation-based parameter estimation framework for a model defined by a computational simulation of a physical system. We

Transformer Transformer: A Unified Model for Motion-Conditioned Robot Co-design

arXiv:2607.25798v1 Announce Type: new Abstract: An often overlooked factor of robot manipulation performance is the embodiment of the robot itself. Motivated by this problem, we study motion-condition

researcharxiv-cs-ro

A Coulomb Particle Model for Learning Kernel Attention in Transformers

arXiv:2607.23869v1 Announce Type: cross Abstract: Randomized features provide a scalable approximation to kernel machines, but their performance depends strongly on the choice of feature distribution.

safetyarxiv-cs-ai

A Few Words Go a Long Way: Language Guided Robot Policy Synthesis

arXiv:2607.23784v1 Announce Type: cross Abstract: While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies tha

Agents

Agentic Reward Modeling: Verifying GUI Agent via Progressive Trajectory-Grounded Interaction

arXiv:2602.00575v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a promising pathway for continuously advancing GUI agents, yet existing reward modeli

agentsarxiv-cs-ro

CALMRec: Causally Aligned Language Memory for Long-Horizon Recommendation

arXiv:2607.23647v1 Announce Type: cross Abstract: Large language models (LLMs) can summarize heterogeneous user evidence in natural language, but current LLM recommenders often collapse enduring prefe

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs

arXiv:2607.22577v1 Announce Type: new Abstract: Scaling large language models (LLMs) has driven their success, yet dense Transformers couple capacity and computation: every parameter is activated for