Search: “models”

eval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models

arXiv:2609.35269v1 Announce Type: cross Abstract: The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods ar

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Models Designed to Forget: Machine Unlearning via Key Deletion

DGX agent

arXiv:2603.15033v4 Announce Type: replace Abstract: Machine unlearning for vision models is rapidly becoming a practical requirement, driven by privacy regulations, data errors, and the need to remove

model-releasesarxiv-cs-lg

29 Sept 2026

Q-WAM: 4-Bit Quantization of World Action Models with Action-Subspace Protection

arXiv:2609.33269v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly generate video and robot actions through iterative diffusion and perform strongly in robotic manipulation. However,

Simplex Diffusion Models

arXiv:2609.35553v1 Announce Type: new Abstract: Diffusion models have revolutionized generative modeling for continuous data through the gradual refinement of a belief state. This iterative refinement

researcharxiv-cs-lg

SLIP-VLA: Single-Step Latent Imagination for Policy Learning in Vision-Language-Action Models

arXiv:2609.33575v1 Announce Type: new Abstract: Vision-Language-Action models are increasingly effective for robotic manipulation, yet most predict actions directly from current observations without e

safetyarxiv-cs-ro

USAI-Quant: A Quantitative Reasoning Benchmark for Vision-Language Models in Built Environments

arXiv:2609.32813v1 Announce Type: new Abstract: Large vision-language models (VLMs) have emerged as a powerful paradigm for urban and spatial AI. However, current state-of-the-art large VLMs still str

When World Models Lie: Adaptive Safety Analysis Under Wrong Imaginations

arXiv:2609.34300v1 Announce Type: new Abstract: World models offer a powerful substrate for safety reasoning in high-dimensional robotic systems, but they are also fallible: their predictions can be b

safetyarxiv-cs-ro

Who Gets a Token, and What Does It Carry? Unequal Name Support and Concept Access in Large Language Models

arXiv:2609.34065v1 Announce Type: cross Abstract: Names are personal identifiers, but they also carry social meaning and are widely used to evaluate how language models treat different people. Such ev

researcharxiv-cs-lg

WorldPlay2: Extending Real-Time Interactive World Models in Control and Horizon

arXiv:2609.35560v1 Announce Type: new Abstract: Interactive world models require responding in real time to versatile controls and maintaining long-horizon consistency. However, modeling heterogeneous

researcharxiv-cs-cv

FLIP: Final Layer Inference-Time Probing for Vision-Language Models

arXiv:2609.30993v1 Announce Type: cross Abstract: We present FLIP, a final-layer inference-time probe for testing whether a logit-facing intervention site in an open-weight vision-language model (VLM)

safetyarxiv-cs-ai

HyperErase: Scale-Calibrated Hypernetwork for Multi-Concept Erasure in Text-to-Image Models

arXiv:2609.31154v1 Announce Type: new Abstract: Recent advances in text-to-image (T2I) generation have substantially improved visual synthesis, but have also raised increasing safety concerns due to t

KneePreM: Towards 3D Knee MRI Foundation Models via Large-Scale Unlabeled Pretraining and Label-Efficient Fine-Tuning

arXiv:2609.31461v1 Announce Type: new Abstract: Background: Large volumes of unlabeled knee MRI scans are available across repositories but remain insufficiently leveraged. We developed KneePreM, a kn

researcharxiv-cs-cv

Applications

NavGen: Visual Generative Models as a Scalable Data Engine for Embodied 3D Navigation

arXiv:2609.30770v1 Announce Type: cross Abstract: General-purpose robot models increasingly rely on large and diverse datasets. For embodied 3D navigation, however, existing data sources face a fundam

applicationsarxiv-cs-ai

OneWorld: Learning Consistent Physics Across Actions in World Models

arXiv:2609.30946v1 Announce Type: cross Abstract: Action-conditioned video world models aim to predict scene evolution under different actions, a capability that is essential for reliable planning, de

Sorry Robot, Happy Human: Vision-Language Models Read Only One of Two Legible Typographic Layers

arXiv:2609.31403v1 Announce Type: cross Abstract: Vision-language models (VLMs), despite their success in optical character recognition (OCR) tasks, are vulnerable to typographic attacks and have a fr

The Plot Twist: Jailbreaking Unified Multimodal Models with a Three-Act NarrativeAttack

arXiv:2509.26473v2 Announce Type: replace Abstract: Unified Multimodal Understanding and Generation Models (UMMs) increasingly combine visual understanding and image generation within a single interac

The Right Information Extraction Pipeline Depends on the Document: Accuracy-Energy Trade-offs for Small, Local Models

arXiv:2609.31341v1 Announce Type: new Abstract: Whether an information extraction pipeline should process page images or parsed text depends on the document, and the answer flips across the layout spe

@WeAreDevs Here's how I define 'Fable class models' - first Claude Fable 5, now Claude Opus 5.5 and GPT-Astra 6 and maybe GPT-5.6 Sol as wel…

model-releasessimon-willison--x

Simon Willison defines “Fable class models” as a lineage of generative AI systems that began with Claude Fable 5, progressed to Claude Opus 5.5, and later included GPT‑Astra 6 (with a possible additio

Adding logit penalty for 'wait', 'maybe' and 'perhaps' to Qwen models improves their accuracy

model-releasesr-localllama

Meta came out with a banger paper https://arxiv.org/pdf/2606.00206, but it did not look at various quantizations supported in llama.cpp. So I did a run on 50 random MATH-500 questions (https://hugging

27 Sept 2026

An interesting idea is to continually train specialized models on skills. This paper explores that idea. They propose SkillGym which turns h…

An interesting idea is to continually train specialized models on skills. This paper explores that idea. They propose SkillGym which turns human-written skills into 2,756 training environments with co

model-releasesdair-ai--x

27 Sept 2026

How accessible is local AI actually, and what happens if affordable access to frontier models doesn’t last?

model-releasesr-localllama

Sometimes it’s easy to forget that this sub and others like it are probably the extreme minority when it comes to this hobby. Most people, I would think, don’t use or can’t afford one good GPU, let al

26 Sept 2026

Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies

arXiv:2609.28670v1 Announce Type: cross Abstract: Graph-based world models have recently emerged as a means of learning transitions over relational state representations. However, existing approaches

Do Audio Language Models Hear and Read Distinctive Features Alike?

arXiv:2609.30167v1 Announce Type: new Abstract: Audio language models pass speech and text through a single decoder. We ask whether that decoder represents a distinctive feature in the same direction

researcharxiv-cs-cl

Large Language Models for Programming: Actually Fixing or Reimplementing Incorrect Code?

arXiv:2609.29410v1 Announce Type: new Abstract: Recent studies have shown that Large Language Models can effectively solve problems and fix bugs in diverse programming environments, including competit

PFArena: Benchmarking Language Models for Protein Modification

arXiv:2609.28921v1 Announce Type: new Abstract: Protein modification requires navigating an immense sequence space, yet wet-lab validation remains low-throughput and costly. Although computational par

Learning When Not to Listen: Selective Anti-Interference Pretraining for Language Models

arXiv:2609.27925v1 Announce Type: new Abstract: Language models can over-condition on irrelevant preceding text: predictions already supported by local context may still change when distant, unrelated

24 Sept 2026

Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning

arXiv:2603.08930v2 Announce Type: replace-cross Abstract: This paper introduces a benchmark for evaluating whether vision-language models (VLMs) can generate plant simulation configurations from image

24 Sept 2026

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

arXiv:2609.23589v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are increasingly used for a broader range of audio reasoning tasks. These models typically incorporate audio repre

Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction

model-releasesarxiv-cs-lg

arXiv:2603.29529v2 Announce Type: replace-cross Abstract: Using a statistical mechanics framework, we investigate the parameter space of transformer models trained on protein sequence data. We sample

SpecialEduBench: Benchmarking Vision-Language Models on Knowledge, Skill, and Attitude in Language Intervention for Autistic Children

arXiv:2609.26090v1 Announce Type: new Abstract: Language is the target of most early intervention for autistic children. Because the goal and the method change from child to child, the work falls to a

The Endless Exam: Mathematical Constructions from Today's Models toward Superintelligence

arXiv:2609.24555v1 Announce Type: new Abstract: We introduce the Endless Exam, a benchmark for measuring mathematical progress from today's models toward artificial superintelligence through fourteen

TriWorldBench: A Tri-View Consistency Perspective on Embodied World Models

model-releasesarxiv-cs-ro

arXiv:2609.26314v1 Announce Type: new Abstract: Embodied world models predict the outcomes of robot actions to support learning and planning. For robots equipped with head and wrist cameras, this requ

Local Ai

What AI models can I realistically run on my GTX 1050 Ti laptop?

Hey everyone, I’m new to running AI models locally and I’d like some advice. My laptop specs are: HP OMEN 15 CPU: Intel i5-8300H RAM: 16 GB GPU: NVIDIA GTX 1050 Ti 4 GB VRAM OS: Windows I’m planning t

local-air-ollama

Local Ai

When Recursive Models Finish Computing

arXiv:2609.26487v1 Announce Type: new Abstract: Recursive models can continue updating their latent states beyond their nominal inference budget, so an incorrect output at that budget does not show wh

local-aiarxiv-cs-lg

ZeroDrift launches three models for real-time AI compliance checks

model-releasessiliconangle

ZeroDrift Inc., a startup that automates compliance for artificial intelligence communications, today launched Anchor 3.0, a family of small language models designed to check messages generated by AI

An Empirical Study and Open Testbed for Federated Fine-Tuning of Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.22973v1 Announce Type: new Abstract: Adapting a pretrained Vision-Language-Action (VLA) model to a new robot, environment, or task requires demonstrations that are collected locally and oft

Do LiDAR Language Models Really Understand Spatio-temporal Relationships?

arXiv:2609.24452v1 Announce Type: new Abstract: Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships. Yet, in our evaluation, always selecting the same

Hardware

KerColle: Unlocking Fine-Grained GPU Concurrency in Vision-Language-Action Models

arXiv:2609.22335v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as foundational models for next-generation robotics. High VLA inference throughput is critical for me

hardwarearxiv-cs-ro

RSPDBench: Benchmarking Vision Foundation Models on Earth Observation Tasks Under Physically Grounded Remote-Sensing Product Degradations

arXiv:2609.23427v1 Announce Type: new Abstract: Vision foundation models targeting Earth observation (EO) tasks are commonly evaluated on clean downstream benchmarks, but operational EO products can a

safetyarxiv-cs-cv

SalQ-VLM: Fine-Grained Saliency-Guided Quantization for Vision-Language Models

arXiv:2508.03351v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse language tasks, motivating their extension to vision-lan

The BD-LSC Dataset: Facilitating the Benchmarking of Models for Lexical Semantic Change Detection in Slang and Standard Usage

arXiv:2606.16560v2 Announce Type: replace Abstract: Automatic semantic change detection aims to identify how word meanings shift over time, offering insights into both linguistic and societal change.

Toward Fairness in Machine Learning Models for Predicting Treatment Retention and Premature Discontinuation in Medication for Opioid Use Disorder

arXiv:2609.22113v1 Announce Type: new Abstract: Persistent low retention and completion rates in medications for opioid use disorder (MOUD) have driven the use of machine learning (ML) models to predi

safetyarxiv-cs-lg

Fact Grounded Attention: Eliminating Hallucination in Large Language Models Through Attention Level Knowledge Integration

arXiv:2509.25252v3 Announce Type: replace Abstract: 'The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge.' Large Language Models have conquered natural language but remai

Industry

JUST IN: Startups are increasingly building custom AI models using open-weight alternatives to cut costs & reduce dependence on OpenAI & Ant…

Recent Bloomberg reports indicate that a growing number of startups are developing custom AI models by leveraging open-weight alternatives to high-cost proprietary platforms like OpenAI’s and Anthropi

industryclem-delangue--x

Meet Wally. Our inference stack for open frontier models, built to be the fastest place to run them. Performance snapshot: GLM-5.3 Flash: 38…

model-releasesyohei-nakajima--x

Meet Wally. Our inference stack for open frontier models, built to be the fastest place to run them. Performance snapshot: GLM-5.3 Flash: 380 tok/s. GLM-5.3 Max: 790 tok/s Qwen3.8-27B: 485 tok/s DeepS

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits

arXiv:2505.10202v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable success but face significant computational and memory challenges, particularly due to their ex

Industry

What I like about Jev: for years, large generalist models sucked almost all the oxygen out of AI. But there are huge opportunities in much m…

What I like about Jev: for years, large generalist models sucked almost all the oxygen out of AI. But there are huge opportunities in much more specialized and customized models, built for specific ta

industryclem-delangue--x

An Analysis of Training-Free Self-Reported Confidence in Language Models

arXiv:2609.20541v1 Announce Type: new Abstract: Large language models can report a numerical confidence together with generated content, but it is unclear whether this report is more than calibrated r