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the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on how to build a harness that's really good at feeding the model

3 Jun 2026

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theUSshould lead on AI by continuing to develop the very best models, making sure they're safe, and getting cyber tools into the hands of tr…

DGX agent

Sam Altman argues that US leadership in artificial intelligence requires three concurrent priorities: advancing cutting-edge AI model development, ensuring these models incorporate robust safety measu

industrysam-altman--x

3 Jun 2026

Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models

arXiv:2606.03748v1 Announce Type: cross Abstract: Real-time vision demands models that are accurate, efficient, and simple to deploy across diverse hardware. The YOLO family has become widely deployed

applicationsarxiv-cs-ai

3 Jun 2026

Value-Aware Stochastic KV Cache Eviction for Reasoning Models

arXiv:2606.03928v1 Announce Type: cross Abstract: Reasoning models improve accuracy through extended chains of thought, but their long outputs create a memory and compute bottleneck. KV cache eviction

3 Jun 2026

A Lightweight Deep Learning-based Model for Ranking Influential Nodes in Complex Networks

arXiv:2507.19702v1 Announce Type: cross Abstract: Identifying influential nodes in complex networks is a critical task with a wide range of applications across different domains. However, existing app

local-aiarxiv-cs-ai

An Algebraic View of the Expressivity of Recurrent Language Models

arXiv:2606.01765v1 Announce Type: cross Abstract: What formal languages can a recurrent neural language model recognize? Formal results in the literature conflict: some authors report Turing-completen

applicationsarxiv-cs-cl

Bayesian meta-learning for modeling Alzheimer's disease progression

arXiv:2606.02228v1 Announce Type: cross Abstract: Predicting whether an individual with Alzheimer's disease will experience mild or severe disease progression is essential for personalized treatment.

applicationsarxiv-cs-cv

BERT4beam: Large AI Model Enabled Generalized Beamforming Optimization

arXiv:2509.11056v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is anticipated to emerge as a pivotal enabler for the forthcoming sixth-generation (6G) wireless communication sy

researcharxiv-cs-lg

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge

arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r

CARTE: A Benchmark for Mapping Language Model Knowledge Across France

model-releasesarxiv-cs-cl

arXiv:2606.01995v1 Announce Type: new Abstract: We introduce CARTE 1 (Culturally Anchored Regional-Territorial Evaluation), a multiplechoice benchmark for evaluating the ability of large language mode

d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation

arXiv:2509.21474v4 Announce Type: replace Abstract: While diffusion language models (DLMs) have achieved competitive performance in text generation, improving their reasoning ability with reinforcemen

safetyarxiv-cs-lg

Decoding in Order-Agnostic Language Models: Chain-Rule Deviation and Uniform Spreading

arXiv:2606.00997v1 Announce Type: new Abstract: Order-agnostic language models (OALMs), including discrete diffusion language models (dLLMs), are trained to predict masked tokens under arbitrary condi

Efficient Test-time Inference for Generative Planning Models

arXiv:2606.00618v1 Announce Type: new Abstract: Generative models have emerged as a powerful paradigm for AI planning, yet their performance remains constrained by the training data distribution. One

Error Bounds for a Diffusion Model-Based Drift Estimator

model-releasesarxiv-cs-lg

arXiv:2606.02115v1 Announce Type: cross Abstract: Parameter estimation in stochastic differential equations is a classical statistical problem of much importance in many scientific fields. Recent work

Evaluating Real-World Generalizability of Algorithm Selection Models

model-releasesarxiv-cs-lg

arXiv:2606.02016v1 Announce Type: new Abstract: Algorithm Selection (AS) aims to automatically identify the most suitable optimization algorithm for a given problem instance by leveraging measurable p

Evaluating the Performance of Deep Learning Models in Whole-body Dynamic 3D Posture Prediction During Load-reaching Activities

arXiv:2511.20615v2 Announce Type: replace-cross Abstract: This study aimed to explore the application of deep neural networks for whole-body human posture prediction during dynamic load-reaching activ

Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays

arXiv:2509.15234v2 Announce Type: replace Abstract: Multimodal learning from paired medical images and clinical text is a central challenge in medical data-driven informatics, where effective cross-mo

Hardware

Eyettention II: A Dual-Sequence Architecture for Modeling Fixation Location, Within-Word Landing Position, and Fixation Duration in Reading

arXiv:2606.01964v1 Announce Type: new Abstract: The way our eyes move while reading provides valuable insights into both the reader's cognitive processes and the properties of the text. In particular,

hardwarearxiv-cs-cl

Failure of contextual invariance in large language models

arXiv:2603.23485v2 Announce Type: replace-cross Abstract: Standard evaluation practices assume that large language model (LLM) outputs are stable when prompts are embedded in contextually equivalent d

FATE-VLA:Failue-aware test generation for vision-language-action models

arXiv:2606.02307v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are increasingly used as generalist robot policies, yet their evaluation still relies largely on static benchmarks t

researcharxiv-cs-ro

Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling

arXiv:2606.01220v1 Announce Type: cross Abstract: Generating molecules that simultaneously satisfy drug-like properties and conform to the 3D structure of a target protein is a core challenge in struc

Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models

arXiv:2602.23197v2 Announce Type: replace Abstract: Transformer-based large language models exhibit in-context learning, enabling adaptation to downstream tasks via few-shot prompting with demonstrati

applicationsarxiv-cs-cl

Hardware

FLARE: Diffusion for Hybrid Language Model

arXiv:2606.01774v1 Announce Type: cross Abstract: Autoregressive (AR) large language models (LLMs) have achieved broad practical success, but sequential decoding remains a key bottleneck for low-laten

hardwarearxiv-cs-ai

From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models

arXiv:2606.00083v1 Announce Type: cross Abstract: Reinforcement learning relies on accurate reward functions, which are often hand-crafted or even unavailable in real-world applications, such as robot

How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models

model-releasesarxiv-cs-cl

arXiv:2511.06676v3 Announce Type: replace Abstract: Now that AI-driven moderation has become pervasive in everyday life, we often hear claims that 'the AI is biased'. While this is often said jokingly

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

arXiv:2606.02573v1 Announce Type: new Abstract: In this paper, we present HumanNOVA, a photorealistic, universal, and rapid model for generating 3D human avatars from a single RGB image. Achieving bot

researcharxiv-cs-cv

Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation

arXiv:2606.02486v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models generalize across static manipulation but fail when objects move during task execution. They map the current observa

researcharxiv-cs-ro

Lessons from the Trenches on Reproducible Evaluation of Language Models

arXiv:2405.14782v3 Announce Type: replace Abstract: Reliable evaluation of language models (LMs) remains an open challenge. Re- searchers and engineers face methodological issues such as the sensitivi

Limits of Spatial Imagery Reasoning in Frontier LLM Models

arXiv:2603.26779v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, yet they struggle with spatial tasks that require mental sim

Physics-Encoded Inverse Modeling for Arctic Snow Depth Prediction

arXiv:2601.17074v4 Announce Type: replace-cross Abstract: Accurate estimation in time-varying inverse problems under limited and sparse observations remains a fundamental challenge across scientific d

Physics-Informed Modeling and Control of Emergent Behaviors in Robot Swarms

arXiv:2606.01597v1 Announce Type: new Abstract: Robot swarms can exhibit coherent collective behaviors through local perception, limited communication and decentralized decision-making, yet modeling a

local-aiarxiv-cs-ro

Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling

arXiv:2505.17659v4 Announce Type: replace-cross Abstract: Safe and feasible trajectory planning is critical for real-world autonomous driving systems. However, existing learning-based planners rely he

Policy and World Modeling Co-Training for Language Agents

arXiv:2606.02388v1 Announce Type: cross Abstract: Reinforcement learning (RL) improves large language model (LLM) agents by teaching them which actions lead to high rewards, but provides little superv

PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning

arXiv:2507.08064v3 Announce Type: replace-cross Abstract: As multimedia content expands, the demand for unified multimodal retrieval (UMR) in real-world applications increases. Recent work leverages m

RAIGen: Rare Attribute Identification in Text-to-Image Generative Models

arXiv:2602.06806v2 Announce Type: replace Abstract: Text-to-image diffusion models achieve impressive generation quality but inherit and amplify training-data biases, skewing coverage of semantic attr

safetyarxiv-cs-cv

ResMerge: Residual-based Spectral Merging of Large Language Models

arXiv:2606.02252v1 Announce Type: new Abstract: Model merging offers a training-free way to combine multiple post-trained expert models, but merging experts obtained through reinforcement learning (RL

Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints

arXiv:2604.01841v2 Announce Type: replace Abstract: Clinical prediction from structured electronic health records (EHRs) is challenging due to high dimensionality, heterogeneity, class imbalance, and

RuleEdit: Failure-Guided Human-AI Model Editing with Prospective Impact Preview

arXiv:2606.00011v1 Announce Type: cross Abstract: Despite the promise of AI to assist complex decisions, practitioners still lack ways to detect likely failures and inspect the consequences of model e

local-aiarxiv-cs-ai

See, Plan, Rewind: Progress-Aware Vision-Language-Action Models for Robust Robotic Manipulation

arXiv:2603.09292v2 Announce Type: replace-cross Abstract: Measurement of task progress through explicit, actionable milestones is critical for robust robotic manipulation. This progress awareness enab

Single-Channel Tissue Segmentation via Cross-Modal Distillation from Foundation Models

arXiv:2606.00928v1 Announce Type: new Abstract: Multiplexed fluorescence microscopy improves tissue segmentation by providing complementary channels including nuclear (DAPI) and membrane (E-cadherin),

StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement

arXiv:2606.00267v1 Announce Type: cross Abstract: Video world models (WMs) have shown promise for policy evaluation and improvement by imagining realistic future observations conditioned on ego-robot

Today we're announcing that hybrid agentic inference is coming to Perplexity Computer. Computer can split tasks between a local model runnin…

Today we're announcing that hybrid agentic inference is coming to Perplexity Computer. Computer can split tasks between a local model running on your machine and frontier models in the cloud. This kee

local-aiperplexity--x

Understanding the Effects of Distractors on Reasoning Vision-Language Models

arXiv:2511.21397v2 Announce Type: replace-cross Abstract: How does irrelevant information (i.e., distractors) affect test-time scaling in vision-language models (VLMs)? Prior work on text-only languag

VESTA: Visual Exploration with Statistical Tool Agents

arXiv:2606.00384v1 Announce Type: new Abstract: Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems lev

AR Forcing: Towards Long-Horizon Robot Navigation World Model

arXiv:2605.31314v1 Announce Type: new Abstract: The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during pa

researcharxiv-cs-ro

Chain-of-Thought Reasoning In The Wild Is Not Always Faithful

arXiv:2503.08679v5 Announce Type: replace Abstract: Recent studies indicate that when faced with explicit biases in prompts, models often omit mentioning these biases in their Chain-of-Thought (CoT) o

Configurable Reward Model for Balanced Safety Alignment

arXiv:2605.30487v1 Announce Type: new Abstract: Aligning large language models (LLMs) to heterogeneous and rapidly evolving safety requirements remains a critical challenge. Existing instruction-tuned

safetyarxiv-cs-cl

Does Visual Information Play a Decisive Role in Vision-Language-Action Model Driving Behavior?

arXiv:2605.31041v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated promising capability in autonomous driving, highlighting the potential of unified multimodal arc