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Power and Limitations of Aggregation in Compound AI Systems

arXiv:2602.21556v2 Announce Type: replace Abstract: When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the responses to produce a synthes

agentsarxiv-cs-ai

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Clear filters

ppl often ask what i'm looking at for investing. here's what's showing up in my pipeline today

DGX agent

Yohei Nakajima shares his current investment pipeline and opportunities he's evaluating, providing insight into the types of ventures and sectors capturing his attention as an investor. The post likel

agentsyohei-nakajima--x

9 Jul 2026

Practicing with Language Models Cultivates Human Empathic Communication

arXiv:2603.15245v2 Announce Type: replace Abstract: Empathy is central to human connection, yet people often struggle to express it effectively. In blinded evaluations, large language models (LLMs) ge

researcharxiv-cs-cl

Predicting LLM Safety Before Release by Simulating Deployment

arXiv:2607.07184v1 Announce Type: cross Abstract: Pre-deployment safety evaluations aim to inform the downstream risks of releasing a new AI model. Yet most evaluations provide limited evidence about

PriGo: Test-Time Primitive Guidance to Diffusion and Flow Policies for Adaptive Robotic Manipulation

arXiv:2607.07076v1 Announce Type: new Abstract: Imitation learning has enabled remarkable progress in robotic manipulation, especially with diffusion and flow-based policies that generate complex visu

applicationsarxiv-cs-ro

Hardware

Prime Intellect raises 130M at 1B valuation for its AI training platform

Artificial intelligence training startup Prime Intellect Inc. has raised 130 million in funding from a group of prominent investors. The consortium included Nvidia Corp.’s NVentures, Intel Capital and

hardwaresiliconangle

Prior-aware and Context-guided Group Sampling for Active Probabilistic Subsampling

arXiv:2607.07083v1 Announce Type: cross Abstract: Subsampling significantly reduces the number of measurements, thereby streamlining data processing and transfer overhead, and shortening acquisition t

applicationsarxiv-cs-lg

Prior-matched evaluation of operational Earth-observation classifiers: a three-number reporting method demonstrated on Sentinel-1 internal-wave detection

arXiv:2607.07146v1 Announce Type: cross Abstract: The Internal Waves Service screens the Sentinel-1 Wave-mode archive for internal solitary waves, routing detections to experts whose adjudication time

researcharxiv-cs-cv

PrismML shrunk Qwen 3.6 to 27B parameters and ran it on an iPhone 17 Pro, bigger than any prior mobile model; sources: Apple talked with PrismML about its tech (Aaron Tilley/The Information)

Aaron Tilley / The Information: PrismML shrunk Qwen 3.6 to 27B parameters and ran it on an iPhone 17 Pro, bigger than any prior mobile model; sources: Apple talked with PrismML about its tech — Apple

model-releasestechmeme

Programmable Synchronization Graphs for Adaptive and Fault-Tolerant Modular Miniature Robots

model-releasesarxiv-cs-ro

arXiv:2607.07281v1 Announce Type: new Abstract: Modular miniature robots could provide scalable function in constrained environments, but coordinating many imperfect modules remains difficult when com

Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production

arXiv:2607.07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously sol

safetyarxiv-cs-ai

ProMoE-FL: Prototype-conditioned Mixture of Experts for Multimodal Federated Learning with Missing Modalities

arXiv:2607.06633v1 Announce Type: cross Abstract: In this paper, we address the problem of multimodal federated learning with missing modality. Existing methods utilize an additional public dataset or

researcharxiv-cs-ai

Prompt: Change the indoor lighting to nighttime, with the indoor environment illuminated by indoor lights.

This post from ComfyUI's Twitter account demonstrates a prompt used within the ComfyUI node-based image generation system to modify lighting in generated scenes. The prompt instructs the AI to render

local-aicomfyui--x

Prompt: Convert the entire collage into a cohesive, realistic interior design photo of a cozy living room. Render the sketched bay window ar…

Prompt: Convert the entire collage into a cohesive, realistic interior design photo of a cozy living room. Render the sketched bay window area on the left into a real window filled with potted plants,

local-aicomfyui--x

Protocol Models: Scaling Decentralized Training with Communication-Efficient Model Parallelism

arXiv:2506.01260v2 Announce Type: replace Abstract: Scaling models has led to significant advancements in deep learning, but training these models in decentralized settings remains challenging due to

Tutorials

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection

arXiv:2607.07192v1 Announce Type: new Abstract: In this paper, we study Single-Domain Generalized Object Detection (Single-DGOD), which aims to transfer a detector trained on a single source domain to

tutorialsarxiv-cs-cv

Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees

arXiv:2405.16668v2 Announce Type: replace Abstract: Adversarial Imitation Learning (AIL) faces challenges with sample inefficiency because of its reliance on sufficient on-policy data to evaluate the

safetyarxiv-cs-lg

PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning

arXiv:2607.06612v1 Announce Type: cross Abstract: Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing use

local-aiarxiv-cs-ai

PUF: Plug-and-Play Uncertainty-Aware Fusion for Online 3D Scene Graph Generation

arXiv:2607.07170v1 Announce Type: new Abstract: Online 3D scene graph generation builds a persistent, structured representation of a scene by incrementally fusing 2D observations into a global 3D grap

researcharxiv-cs-cv

QANTIS: Hardware-Calibrated Sequential POMDP Belief Updates on IBM Heron

arXiv:2607.06760v1 Announce Type: new Abstract: Autonomous systems under partial observability act on beliefs, not raw sensor events. QANTIS treats the quantum processor as a calibrated belief-update

agentsarxiv-cs-ai

QCNN with Rough Path Signature Kernels

arXiv:2607.07634v1 Announce Type: cross Abstract: Time series analysis plays a vital role across a wide range of scientific and engineering domains but poses substantial computational challenges. A ma

researcharxiv-cs-ai

QIZ Security raises $17M seed round for post-quantum readiness platform

Cybersecurity startup QIZ Security Ltd. today announced it has raised 17 million in seed funding to expand a platform that discovers and governs the encryption buried across enterprise systems ahead o

applicationssiliconangle

Quantum simulation of real-world nonlinear dynamics via Koopman method

arXiv:2607.07338v1 Announce Type: cross Abstract: Nonlinear dynamics is ubiquitous in nature, ranging from chemical pattern formation to ocean circulation, yet its simulation on quantum computers is f

applicationsarxiv-cs-ai

R^3: Advertisement Compliance Rectification via Group-Relative Experience Extractor and Curriculum Reinforcement

arXiv:2607.07318v1 Announce Type: new Abstract: Rigorous content moderation is crucial for online advertising but leads to millions of daily rejections. This scale renders manual rectification infeasi

safetyarxiv-cs-cl

Rail Track Extraction from Rasterized Classified Point Clouds Using a Full-Resolution, Fully Convolutional Recurrent Neural Network

arXiv:2607.06829v1 Announce Type: new Abstract: Rail track extraction is essential for effective railway asset management and maintenance, especially in automated inspection and mapping workflows. Thi

researcharxiv-cs-cv

Rapidly Learning Soft Robot Control via Implicit Time-Stepping

arXiv:2511.06667v2 Announce Type: replace-cross Abstract: With the explosive growth of rigid-body simulators, policy learning in simulation has become the de facto standard for most rigid morphologies

safetyarxiv-cs-ai

Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents

arXiv:2607.07405v1 Announce Type: new Abstract: Tool-using LLM agents can violate the very policies they are deployed to enforce while appearing to complete the task successfully. In policy-permissive

Reasoning Consistency Scanning: A Framework for Auditing Chain-of-Thought Validity in AI Safety Evaluations

arXiv:2607.07229v1 Announce Type: new Abstract: Prior work has shown that chain-of-thought (CoT) reasoning is often unfaithful: a model's stated reasoning does not reliably reflect the process that pr

Reconfigurable Radiology Labels Without Relabeling

model-releasesarxiv-cs-cl

arXiv:2607.06597v1 Announce Type: cross Abstract: Public chest-radiograph (CXR) datasets are typically released with small, fixed label schemas such as CheXpert-14. However, the underlying free-text r

Tutorials

Recovering Candidate Circadian Regulators of Arrhythmic Pituitary Hormone Genes Using Reliability-Weighted Magnetic Laplacian with rwMagLap

arXiv:2607.06579v1 Announce Type: cross Abstract: We study how to recover candidate circadian-clock regulators of pituitary hormone genes that are important for women's health but do not show a clear

tutorialsarxiv-cs-lg

Recovering Latent Structures after Variational Bayesian Variable Selection: Fit Assessment and Factor-Number Selection in Partially Exploratory Factor Analysis

model-releasesarxiv-cs-cl

arXiv:2607.07159v1 Announce Type: cross Abstract: In partially exploratory factor analysis (PEFA), the loading structure and factor numbers are weakly specified. The regularized variational approximat

Recursive Language Models Meet Uncertainty: The Surprising Effectiveness of Self-Reflective Program Search for Long Context

Long-context handling remains a core challenge for language models: even with extended context windows, models often fail to reliably extract, reason over, and use the information across long contexts

agentsapple-ml-research

Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops

arXiv:2607.07663v1 Announce Type: new Abstract: AI systems increasingly participate in their own improvement: revising their outputs, adapting their own harnesses during deployment, training on data t

safetyarxiv-cs-ai

Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning

arXiv:2511.13726v2 Announce Type: replace-cross Abstract: We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the fina

Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering

arXiv:2306.12859v3 Announce Type: replace Abstract: Federated learning is a distributed machine learning technology, which realizes the balance between data privacy protection and data sharing computi

Reliable and Developer-Aligned Evaluation of Agents for Software Engineering

arXiv:2607.06713v1 Announce Type: cross Abstract: Large language models are rapidly moving towards closing the development cycle, transitioning from simple assistive companions to autonomous contribut

agentsarxiv-cs-ai

Reliable mechanistic operator recovery with biologically-informed neural networks: principles for architecture and optimisation design

arXiv:2607.07425v1 Announce Type: cross Abstract: Many biological processes are governed by complex dynamical mechanisms that remain incompletely understood despite increasing volumes of experimental

ReMoDEx: A Local-to-Global Relevance-Based Model Decision Explainability Framework for large-Scale Image Datasets

arXiv:2607.06889v1 Announce Type: cross Abstract: Deep learning image classifiers achieve strong predictive performance yet remain opaque in how decisions are formed. A model may predict correctly whi

local-aiarxiv-cs-ai

Tutorials

Research on Domain Information Mining and Theme Evolution of Scientific Papers

arXiv:2204.08476v2 Announce Type: replace-cross Abstract: In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased

tutorialsarxiv-cs-lg

Residual-Conservative Model Predictive Path Integral Control

arXiv:2607.06950v1 Announce Type: cross Abstract: Sampling-based model predictive control methods handle nonlinear dynamics and complex cost landscapes through Monte Carlo rollouts, yet typically empl

safetyarxiv-cs-ro

Restricted Dynamic Geometric Complexity: Certificates for Structured Preconditioning

arXiv:2607.07204v1 Announce Type: cross Abstract: Optimization geometrodynamics views optimizer state as evolving geometry. Its full positive-definite quadratic benchmark gives the least affine-invari

Rethinking Multimodal Time-Series Forecasting Evaluation

arXiv:2607.06973v1 Announce Type: new Abstract: We introduce a new context-enriched, multimodal time series forecasting benchmark, TimesX. TimesX contains a wide selection of high-quality real-world t

Retrieving and Refining Winning Noise Tickets for Diffusion-Based Motion Generation

model-releasesarxiv-cs-cv

arXiv:2607.06843v1 Announce Type: new Abstract: Diffusion-based text-to-motion models synthesize realistic human motions but often exhibit semantic drift from the input text. Motion is inherently temp

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26

arXiv:2607.07498v1 Announce Type: cross Abstract: Testing is a major effort for the gaming industry, requiring a significant part of development budget and people power. We present a case study on a d

applicationsarxiv-cs-ai

Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia

arXiv:2607.06626v1 Announce Type: new Abstract: Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask whether this alignment extends to reward valuation, w

local-aiarxiv-cs-lg

Riemannian Geometry for Pre-trained Language Model Embeddings

arXiv:2607.07047v1 Announce Type: cross Abstract: Understanding the geometric structure of pre-trained language model embeddings matters for interpretability and safety. We ask whether sentence-level

RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning

arXiv:2601.00086v3 Announce Type: replace Abstract: Large language models (LLMs) often struggle to use tools reliably in domain-specific settings, where APIs may be idiosyncratic, under-documented, or

agentsarxiv-cs-cl

RL Post-Training Builds Compositional Reasoning Strategies

arXiv:2607.07646v1 Announce Type: new Abstract: Does RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategie

researcharxiv-cs-ai