Search: “models”

Efficient Code Embeddings from Code Generation Models

arXiv:2508.21290v2 Announce Type: replace-cross Abstract: jina-code-embeddings is a novel code embedding model suite designed to retrieve code from natural language queries, perform technical question

Evidence of conceptual mastery in the application of rules by Large Language Models

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DGX agent

arXiv:2503.00992v2 Announce Type: replace Abstract: In this paper we leverage psychological methods to investigate LLMs' conceptual mastery in applying rules. We introduce a novel procedure to match t

model-releasesarxiv-cs-ai

18 Aug 2026

Learning Auditable Classifier Models: Source-Disjoint Tree Ensembles

arXiv:2608.15725v1 Announce Type: new Abstract: Predictive models in clinical and regulated settings must be accurate and fully auditable. Tree ensembles deliver strong accuracy on tabular data, but t

researcharxiv-cs-lg

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as

applicationsarxiv-cs-lg

Revisiting Classifier-Free Guidance Methods in Latent Diffusion Models

arXiv:2608.16786v1 Announce Type: new Abstract: Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We stud

safetyarxiv-cs-cv

Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature

arXiv:2402.01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often

17 Aug 2026

Agents

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

arXiv:2608.13472v1 Announce Type: cross Abstract: Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition.

agentsarxiv-cs-ai

14 Aug 2026

Into the ORBIT for Time Series: Training Regimes for Foundation Models

arXiv:2608.13262v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have advanced primarily through architectural innovation, while training regimes for large-scale heterogeneous c

14 Aug 2026

Open models are improving at an unprecedented rate. Congrats to the whole @Zai_org team. Ollama will support GLM-5.3 upon the open release! …

Open models are improving at an unprecedented rate. Congrats to the whole @Zai_org team. Ollama will support GLM-5.3 upon the open release! ❤️ Get ready to code. Introducing GLM-5.3: Built to Code. Re

local-aiollama--x

14 Aug 2026

CLAIM: Leading Open-domain Active Clarification of Large Language Models with Uncertainty Measurement

arXiv:2608.11631v1 Announce Type: new Abstract: In open-domain human-computer interaction scenarios, large language models (LLMs) frequently encounter user queries that are ambiguous or incomplete. In

Distillation of Foundation Models for Time-dependent PDEs

arXiv:2608.11937v1 Announce Type: new Abstract: Foundation models for time-dependent partial differential equations (PDEs) are trained on large and diverse collections of physical systems and can gene

local-aiarxiv-cs-lg

Agents

I think this will turn out to be wrong, and not just because I suspect there are greater returns to more intelligent models than people expe…

I think this will turn out to be wrong, and not just because I suspect there are greater returns to more intelligent models than people expect Economic value comes from agents, not chatbots. And accur

agentsethan-mollick--x

OEIS Open: How many conjectures can language models turn into theorems?

model-releasesarxiv-cs-ai

arXiv:2608.11941v1 Announce Type: new Abstract: We construct OEIS Open, a benchmark based on 492 open mathematical conjectures from the OEIS, formalized in Lean by Tsoukalas et al. Whereas these conje

RLinf-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models

arXiv:2510.06710v3 Announce Type: replace Abstract: Recent studies have demonstrated the potential of reinforcement learning (RL) to improve the task performance of vision-language-action (VLA) models

researcharxiv-cs-ro

Towards Human Motion World Models via Executable Behaviour Representations

arXiv:2604.18064v2 Announce Type: replace Abstract: Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion

Graphical Models of False Information and Fact Checking Ecosystems

arXiv:2208.11582v2 Announce Type: replace-cross Abstract: The wide spread of false information online, including misinformation and disinformation, has become a major problem for our highly digitised

applicationsarxiv-cs-ai

Hybrid Token Compression for Vision-Language Models

arXiv:2512.08240v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs. Existing compression methods

Logit Lens Supervision for Patch-Level Explanations in Vision-Language Models

arXiv:2602.01530v2 Announce Type: replace Abstract: Modern autoregressive Vision-Language Models (VLMs) can generate fluent answers while their visual-token representations become weakly tied to the i

Agents

On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models

arXiv:2608.10530v1 Announce Type: cross Abstract: Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool

agentsarxiv-cs-ai

VIScore: Diagnosing Planning-Relevant Quality in Latent World Models

arXiv:2608.11174v1 Announce Type: new Abstract: Regulating the latent space to an isotropic Gaussian distribution provides a stable and information-maximized landscape for world model planning. Howeve

researcharxiv-cs-ro

AgriField-40K: Adapting Vision Models to Agriculture With Efficient Continual Pretraining

model-releasesarxiv-cs-cv

arXiv:2608.07984v1 Announce Type: new Abstract: Field-based agricultural computer vision is important for precision agriculture, yet it largely depends on expensive annotations and costly adaptation o

Auditing Medical Vision-Language Models on Chest Radiographs: Estimating Reference Agreement Across Institutions

arXiv:2608.07550v1 Announce Type: new Abstract: Vision-language models return structured chest-radiograph findings through interfaces exposing no confidence score, so a receiving institution cannot re

local-aiarxiv-cs-cv

Commitment Before Realization: When Classifier-Free Guidance Becomes Unnecessary in Masked Diffusion Language Models

arXiv:2608.08082v1 Announce Type: new Abstract: Classifier-free guidance (CFG) is usually kept on throughout masked diffusion language model decoding, although its benefit varies across prompts and ov

researcharxiv-cs-cl

Distilling Physical Priors into Streaming World Models

arXiv:2608.07981v1 Announce Type: new Abstract: Streaming world models predict future visual states online while maintaining physically coherent dynamics over long horizons. However, their rollouts of

applicationsarxiv-cs-cv

Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles

arXiv:2608.08815v1 Announce Type: new Abstract: Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable

safetyarxiv-cs-lg

DreOPD: Degraded-Reference Extrapolative On-Policy Distillation for Flow-matching Models

arXiv:2608.09233v1 Announce Type: cross Abstract: Flow-matching models are now a mainstream method to image generation, but its adaptation to diverse downstream scenarios typically relies on post-trai

safetyarxiv-cs-cv

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning

arXiv:2608.09876v1 Announce Type: cross Abstract: Physically consistent motion planning remains a fundamental challenge in embodied AI, as generated trajectories must strictly conform to real-world ex

HarnessWAM: Bridging Prediction and Deliberation in World Action Models

arXiv:2608.09516v1 Announce Type: new Abstract: World Action Models (WAMs) jointly learn environmental dynamics and robot actions, introducing priors over physical evolution into embodied control. How

local-aiarxiv-cs-ro

Length-MAX Tokenizer for Language Models

arXiv:2511.20849v2 Announce Type: replace-cross Abstract: We introduce a new tokenizer for language models that minimizes the average tokens per character, thereby reducing the number of tokens needed

applicationsarxiv-cs-ai

Mechanistic Interpretability-Guided Selective Fine-Tuning of Vision-Language Models for Centimeter-Level Flood Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2608.07562v1 Announce Type: new Abstract: Urban flooding poses an escalating threat to transportation infrastructure, yet no operational system provides real-time, street-level flood-depth estim

Persuasive and Compliant Tendencies Predict Group Decision-Making in Humans and Language Models

arXiv:2608.08199v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly involved in group decision-making with other LLMs and humans. Yet it remains unclear whether their influen

Sign Language Recognition Using Original and Synthetic Depth Image Based Point Cloud Data Models

arXiv:2608.09400v1 Announce Type: cross Abstract: Research regarding the sign language recognition mostly relies on RGB images, whileas sign language datasets that provide depth images are limited. Po

Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understanding

model-releasesarxiv-cs-ai

arXiv:2608.08512v1 Announce Type: new Abstract: Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has diff

Topographic Constraints Shape Brain-Like Component Structure in Auditory Models

arXiv:2509.24039v2 Announce Type: replace-cross Abstract: If topography is a fundamental feature of the brain, it should influence both how neurons are arranged in space (i.e. explain brain maps) and

HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Models

arXiv:2608.07003v1 Announce Type: new Abstract: Training-free text-to-high-resolution image generation has recently attracted growing research attention. However, existing studies on this task primari

Hardware

If Anthropic begin shipping chips, will NVIDIA begin shipping frontier models? Who will win?

hardwareitamar-friedman--x

On August 10 2026 at 1:39 AM UTC, user Itamar Friedman (@itamar_mar) posted a short tweet asking whether Anthropic’s potential launch of its own chips would prompt NVIDIA to release frontier AI models

Prune Once: Retraining-Free Task-Agnostic Pruning for Vision-Language Models

arXiv:2608.06901v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable generalization across diverse multimodal tasks through large-scale pre-training, yet their rapidl

Unsupervised Adaptation of PDE Foundation Models

arXiv:2608.07053v1 Announce Type: new Abstract: Pretrained partial differential equation (PDE) foundation models can generalize across different equations, but adapting them to unseen PDE systems typi

Tools

Voyage AI models now run natively on Fireworks, the first and only dedicated inference platform @VoyageAI by @MongoDB has partnered with. Em…

Voyage AI models now run natively on Fireworks, the first and only dedicated inference platform @VoyageAI by @MongoDB has partnered with. Embed, retrieve, rerank, generate: your full retrieval pipelin

toolsfireworks-ai--x

Industry

Hugging Face is getting one new repository every seven seconds. That is roughly 12,000 new models and datasets a day, every day. Clem Delang…

Hugging Face is getting one new repository every seven seconds. That is roughly 12,000 new models and datasets a day, every day. Clem Delangue @ClementDelangue said it on stage at AMD's developer conf

industryclem-delangue--x

9 Aug 2026

Do Tabular Foundation Models Agree with Themselves?

arXiv:2608.06004v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) are currently the best approach to tabular prediction problems. They are constructed as transformers that approximate t

applicationsarxiv-cs-lg

How Far Do Simple Transformations Translate Across Text Embedding Models?

arXiv:2608.05980v1 Announce Type: new Abstract: We investigate whether simple transformations can translate representations across heterogeneous text embedding models. Understanding how independently

researcharxiv-cs-lg

In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use

arXiv:2608.05738v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become the dominant recipe for generalist manipulation, yet they are almost universally trained by behavior clo

safetyarxiv-cs-ro

KVAE: Family of Tokenizers for Multimodal Generative Models

arXiv:2608.05798v1 Announce Type: new Abstract: Latent diffusion modeling (LDM), a prominent paradigm, utilizes tokenizers to map input signal to compressed representation. This dependency positions t

LUNAR: Benchmarking Personalized Large Language Models on UNiversal User BehAvioR Logs

model-releasesarxiv-cs-ai

arXiv:2608.05246v1 Announce Type: new Abstract: Existing personalized LLM benchmarks primarily rely on textual personas or isolated behavioral signals, providing limited evaluation of cross-domain beh

Tutorials

Mapping Similarity Spaces across Embedding Models with Synthetic Query Probing

arXiv:2608.05857v1 Announce Type: new Abstract: Retrieval-Augmented Generation systems rely on similarity scores to retrieve relevant content, yet scores are not directly comparable across embedding m

tutorialsarxiv-cs-cl

Tutorials

Mean-Field Dynamics of Chain-of-Thought Reasoning in Large Language Models

arXiv:2608.05152v1 Announce Type: cross Abstract: Large language models (LLMs) with chain-of-thought reasoning have been widely applied in recent years, and theoretical explanations of their behavior

tutorialsarxiv-cs-ai

PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models

arXiv:2608.05720v1 Announce Type: new Abstract: We propose PhyLatent, a dynamics-relevant training objective for JointEmbedding Predictive Architecture (JEPA) world models. Our key observation is that

safetyarxiv-cs-cv