Search: “models”

LIBERO-Occ: Evaluating and Improving Vision-Language-Action Models under Scene-Induced Occlusion via Viewpoint Imagination

arXiv:2606.10862v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong performance on standard manipulation benchmarks, but most evaluations assume that task-relevant obj

Model Releases

Parametric Knowledge is Not All You Need: Toward Honest Large Language Models via Retrieval of Pretraining Data

DGX agent

arXiv:2601.21218v2 Announce Type: replace Abstract: Large language models (LLMs) are highly capable of answering questions, but they are often unaware of their own knowledge boundary, i.e., knowing wh

model-releasesarxiv-cs-cl

10 Jun 2026

ReflectiChain: Epistemic Grounding in LLM-Driven World Models for Supply Chain Resilience

arXiv:2606.10359v1 Announce Type: new Abstract: AI agents in supply chains face a fundamental epistemic gap: large language models (LLMs) interpret policies but lack physical grounding, while reinforc

Applications

Rod models in continuum and soft robot control: a review

arXiv:2407.05886v3 Announce Type: replace Abstract: Continuum and soft robots can transform automation tasks requiring compliant interaction in constrained or unstructured environments, including heal

applicationsarxiv-cs-ro

Agents

Vehicle Prediction Model for Enhanced MPC Path Tracking in Formula Student Driverless

arXiv:2606.10732v1 Announce Type: new Abstract: Autonomous race cars, such as in Formula Student Driverless, operate close to their physical handling limits. The resulting highly nonlinear vehicle beh

agentsarxiv-cs-ro

When Metrics Disagree: A Meta-Analysis of Knowledge-Graph-Completion Model Benchmarking

arXiv:2606.10287v1 Announce Type: cross Abstract: Evaluating Knowledge Graph Completion (KGC) models remains challenging because standard assessment relies on isolated rank-based metrics such as MRR,

researcharxiv-cs-cl

Bayesian Optimization of a Multi-Product Chemical Reactor Using Composite Models and Partial Physics Knowledge

model-releasesarxiv-cs-lg

arXiv:2606.08611v1 Announce Type: cross Abstract: We study data-driven real-time economic optimization of a multi-product chemical reactor when no reliable first-principles model is available beyond a

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

model-releasesarxiv-cs-lg

arXiv:2606.09401v1 Announce Type: new Abstract: Recent work has applied differential privacy (DP) to adapt large language models (LLMs) for sensitive applications, offering theoretical guarantees. How

BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving

arXiv:2606.08684v1 Announce Type: new Abstract: We present BLUE, a minimal method for better language use in vision-language-action (VLA) models for autonomous driving (AD). Through extensive analysis

@cohere Nice! Great to see another open source model released. 🙌

Cohere announced the release of another open source model, receiving positive reception from the community. The post was shared on X (formerly Twitter) and highlights Cohere's continued contribution t

model-releasescohere--x

Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency Without Model Sweeps

model-releasesarxiv-cs-lg

arXiv:2510.12744v2 Announce Type: replace-cross Abstract: We develop a unified statistical framework for softmax-gated Gaussian mixture of experts (SGMoE) that addresses three long-standing obstacles

DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home

arXiv:2606.07542v1 Announce Type: cross Abstract: Generative AI is reshaping healthcare, yet most existing advances rely on hospital-grade devices, which limits their accessibility and potential for h

Dream-Tac: A Unified Tactile World Action Model for Contact-Rich Robot Manipulation

arXiv:2606.08737v1 Announce Type: new Abstract: World action models inherit the predictive capability of world models, enabling action generation to be guided by anticipated future observations. Howev

safetyarxiv-cs-ro

From `May' to `Is': Certainty Distortion in Language Model Rewriting

arXiv:2606.07951v1 Announce Type: cross Abstract: Humans increasingly turn to Language Models (LMs) in ways that shape beliefs and drive decisions, including discussing, rewriting, and summarizing inf

GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model Recommendation

arXiv:2606.07526v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong potential for recommendation (LLMRec) due to their powerful reasoning and generalization abilities. How

Introducing Gemma 4 12B: a unified, encoder-free multimodal model

model-releasesgoogle-deepmind

Gemma 4 12B is a unified, encoder-free multimodal model designed to bring high-performance intelligence to laptops and released under an Apache 2.0 license. It eliminates separate encoders by projecti

LEAF: Growing Trees Without Branching for Speech-Aware Large Language Model Post-Training

arXiv:2606.07610v1 Announce Type: cross Abstract: State-of-the-art GRPO-style methods for speech-aware large language model post-training suffer from coarse credit assignment, broadcasting the same te

MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models

arXiv:2606.07706v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated strong performance across multimodal tasks, yet their safety robustness remains an open challenge. Whi

Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers

arXiv:2601.12263v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) integrate visual and textual knowledge into unified representations that increasingly underpin modern retrieval

safetyarxiv-cs-ai

Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation

arXiv:2606.07541v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong performance on objective tasks such as video understanding and reasoning. However, it remai

Phantom transitions in language model fine-tuning

arXiv:2606.07559v1 Announce Type: cross Abstract: Fine-tuning a language model on contexts whose correct completion has a near-synonym competitor often fails silently. The cross-entropy loss decreases

POTATR: A Lightweight Image-to-Graph Model for Page-Level Table Extraction

arXiv:2606.09788v1 Announce Type: new Abstract: Large-scale document processing requires contextually aware table extraction (TE) that is both accurate and efficient. Yet current approaches require bi

Rank Intervals for Leaderboards: A Hierarchical Framework for Model Evaluation

arXiv:2606.08679v1 Announce Type: cross Abstract: Pretrained models are often evaluated on multi-task leaderboards to measure their applicability in diverse contexts. However, current methods for aggr

researcharxiv-cs-lg

Scaling by Diversified Experience for Vision-Language-Action Models

arXiv:2606.09009v1 Announce Type: new Abstract: Vision-Language-Action models face significant challenges in real-world deployment due to the entanglement of high-level reasoning with low-level contro

See how Claude Fable 5 compares across every model: http://cursor.com/evals

Claude Fable 5 is compared against other AI models on various evaluation metrics through Cursor's benchmarking tool. The evaluation likely covers performance across different tasks such as coding, rea

model-releasescursor--x

Should Demand Models Incorporate Competitor Prices? Oblivious Learning and Algorithmic Collusion

arXiv:2606.05363v2 Announce Type: replace-cross Abstract: On a platform with many sellers, should a pricing algorithm explicitly model competitors' prices when learning demand? Classical learning argu

researcharxiv-cs-lg

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models

arXiv:2606.07861v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored.

Unified Energy for Invariant and Independent Decoding in Diffusion Language Models

arXiv:2606.09159v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) enable parallel text generation by iteratively denoising a full sequence, offering attractive flexibility compared to

researcharxiv-cs-ai

We talk a lot about how important it is to set up self-verification loops. Especially in the age of powerful models that can run for long pe…

model-releasesboris-cherny--x

We talk a lot about how important it is to set up self-verification loops. Especially in the age of powerful models that can run for long periods of time, self-verification is a key ingredient that en

ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model

model-releasesarxiv-cs-ro

arXiv:2511.12795v2 Announce Type: replace Abstract: Grasping in a densely cluttered environment is a challenging task for robots. Previous methods tried to solve this problem by actively gathering mul

Beyond Rubrics: Exploration-Guided Evaluation Skills for Reward Modeling

arXiv:2606.07040v1 Announce Type: new Abstract: Open-ended reward modeling requires judges that can follow subtle, domain-specific preferences when verifiable answers are unavailable. Existing rubric-

Diagnosing Visual Ignorance in Vision-Language Models

arXiv:2606.06890v1 Announce Type: new Abstract: Vision-Language Models (VLMs) frequently rely on language priors, producing confident answers that are weakly grounded in visual evidence. While this be

Elmes*: Automated Construction of Fine-Grained Evaluation Rubrics for Large Language Models in Long-Tail Educational Scenarios

arXiv:2606.06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know. Existing benchmarks emphasize domain

safetyarxiv-cs-lg

Hardware

Good take My guess is - demand for intelligence is near infinite - but 80% of workloads will be running on 99% cheaper models within 12-18 m…

Good take My guess is - demand for intelligence is near infinite - but 80% of workloads will be running on 99% cheaper models within 12-18 months - 20% of workloads will still run on latest gen models

hardwareclem-delangue--x

GuideCAD: A Lightweight Multimodal Framework for 3D CAD Model Generation via Prefix Embedding

arXiv:2606.07024v1 Announce Type: new Abstract: Multi-modal approaches used for 3D CAD generation require substantial computational resources, necessitating efficient training. To address this, we pro

Have been extensively testing Claude Workflows this weekend, with the best model possible. Threw it at my whole code base, combing for bugs.…

model-releasesboris-cherny--x

Have been extensively testing Claude Workflows this weekend, with the best model possible. Threw it at my whole code base, combing for bugs. 144 found and fixed! Geez... It is a large code base, for s

7 Jun 2026

Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field deformation data

arXiv:2606.05199v1 Announce Type: cross Abstract: The identification of constitutive neural network models from heterogeneous full-field deformation data provides a robust alternative to traditional c

researcharxiv-cs-ai

LatentWave: JEPA Pretraining for Wireless Foundation Models

arXiv:2606.06373v1 Announce Type: cross Abstract: Wireless foundation models have emerged as a promising alternative to building separate models for each wireless task. However, existing approaches re

safetyarxiv-cs-ai

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models

arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigi

The Gemini Pro models do not seem to be iterating anywhere near as quickly as Claude or GPT (last release was 3.1 Pro in February). Its caus…

model-releasesethan-mollick--x

The Gemini Pro models do not seem to be iterating anywhere near as quickly as Claude or GPT (last release was 3.1 Pro in February). Its causing a growing performance gap between Google and the other t

Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models

arXiv:2606.05481v1 Announce Type: cross Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining usefu

researcharxiv-cs-ai

Local Ai

AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding

arXiv:2606.06155v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robo

local-aiarxiv-cs-cv

Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models

arXiv:2606.05531v1 Announce Type: cross Abstract: Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagnose their true reasoning abilities and ch

Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution

arXiv:2606.06492v1 Announce Type: cross Abstract: Code language models need repository-level context to resolve imports, APIs, and project conventions. Existing methods inject this knowledge as long i

Gemma 4 Quantization-Aware Training (QAT) weights are now available on Ollama! They reduce memory requirements while maintaining model quali…

Gemma 4 Quantization-Aware Training (QAT) weights are now available on Ollama! They reduce memory requirements while maintaining model quality. E2B: ollama run gemma4:e2b-it-qat E4B: ollama run gemma4

model-releasesollama--x

MASF: A Multi-Model Adaptive Selection Framework for Abstractive Text summarization

arXiv:2606.05494v1 Announce Type: new Abstract: Automatic text summarization has become increasingly important due to the rapid growth of digital textual information. This paper presents a Multi-Model

researcharxiv-cs-cl

Agents

Merging model-based control with multi-agent reinforcement learning for multi-agent cooperative teaming strategies

arXiv:2606.06011v1 Announce Type: new Abstract: In this work, we propose a framework that combines multi-agent reinforcement learning (MARL) with model-based control to achieve safe, dynamically feasi

agentsarxiv-cs-ro

PlanBench-V: A Spatial Planning Map Benchmark for Vision-Language Models

arXiv:2606.05744v1 Announce Type: new Abstract: Spatial planning maps are central to territorial governance, translating planning objectives, regulations, and spatial strategies into visual forms for