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PB^2: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning

arXiv:2506.13741v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PbRL) has emerged as a promising approach for learning behaviors from human feedback without predefin

agentsarxiv-cs-lg

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Pc build limitations

DGX agent

Here's the build I managed to scrape together System Specifications: CPU: Intel Core i7-7700K Motherboard: ASUS ROG Strix Z270-E Gaming RAM: 32GB Corsair Vengeance DDR4-3000 Storage: 1TB Crucial P5 Pl

model-releasesr-ollama

4 Aug 2026

Applications

PeCA: Palette Context Assisted Inference for Test-Time Paint-Bucket Colourisation on Animation Videos

arXiv:2608.00903v1 Announce Type: new Abstract: In animation production, paint-bucket colourisation for hand-drawn animation is a labour-intensive procedure that assigns each enclosed region in line s

applicationsarxiv-cs-cv

Perception-and-action system for humanoid robot task execution in construction

arXiv:2608.01600v1 Announce Type: new Abstract: Humanoid robots, with their human-like shape and multi-tasking capabilities, are well-aligned with human-dominated workplaces, like those in civil and c

tutorialsarxiv-cs-ro

PGMem: Tightly Coupled Persona-Memory Graph for Lifelong Personalized Agents

arXiv:2608.01708v1 Announce Type: new Abstract: Long-term personalized dialogue agents must track user preferences as their personas evolve. Existing memory systems organize past events well, but stor

agentsarxiv-cs-cl

PhenoStitch: Training-Free Panoptic Crop Mapping from Satellite Image Time Series

arXiv:2608.00870v1 Announce Type: new Abstract: Panoptic crop mapping requires both delineating individual agricultural parcels and assigning a crop type to each parcel from satellite image time serie

Applications

PhotoHOI: Synthesizing 3D Hand-Object Interactions from a Single RGB Photograph

arXiv:2608.01905v1 Announce Type: new Abstract: Hand-object interaction (HOI) is a fundamental human behavior with broad applications in AR/VR, digital humans, and embodied interaction. Existing metho

applicationsarxiv-cs-cv

PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs

arXiv:2608.02150v1 Announce Type: new Abstract: Embodied intelligence and world models require video understanding systems to go beyond recognizing objects and actions and develop an understanding of

PhysAgent: A Multi-Agent Framework for Reliable Remote Heart Rate Estimation

model-releasesarxiv-cs-cv

arXiv:2608.00066v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact heart-rate estimation from facial videos, but its weak physiological signal is easily corrupted b

Physical Self-Supervised Learning: IMU Sensing without Manual Labels

arXiv:2607.18361v2 Announce Type: replace Abstract: Deep neural networks have become a promising approach for IMU-based sensing, but their scalability is fundamentally limited by costly labeled data a

Picking the right agent harness is now a crucial skill for any AI engineer. Imagine using the same model, same task, and same prompt. Now mo…

Picking the right agent harness is now a crucial skill for any AI engineer. Imagine using the same model, same task, and same prompt. Now move it between two agent harnesses and the cost per success c

model-releasesdair-ai--x

PICTURE: Enhancing Theory-of-Mind in Large Language Models by Revealing, Not Hiding, Characters' Lack of Knowledge

arXiv:2608.01598v1 Announce Type: new Abstract: Simulating human-like Theory of Mind (ToM) has been a longstanding problem in natural language processing (NLP). To address this, existing works introdu

PipeNetwork/minimax-h3-mlx

model-releasessimon-willison

PipeNetwork/minimax-h3-mlx MiniMax released MiniMax-H3 two days ago - they describe it as a 'a general-purpose, omni-modal generative system', which in practice means it accepts text, images, audio an

Pixel Ignores, Superpixel Sees: Adverse Weather Image Restoration via Semantic-Center SSM

arXiv:2608.01760v1 Announce Type: new Abstract: Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to address

Local Ai

PixelSR: Efficient Screen Content Super-Resolution via Pixel Classification

arXiv:2608.00646v1 Announce Type: new Abstract: Screen content images are generally composed of texts and graphics. Compared to natural images, these man-made images contain a large quantity of sharp

local-aiarxiv-cs-cv

PixVL: Self-Supervised Training of Pixel-Level MLLMs via a Unified Mask--Text Consistency Cycle

arXiv:2608.01354v1 Announce Type: new Abstract: Recent studies develop pixel-level multimodal large language models (MLLMs) that support both Region Segmentation and Region Understanding, extending mu

tutorialsarxiv-cs-cv

PlainMedScale: A Corpus of Multi-Level Simplified Medical Texts in German and English

arXiv:2608.01158v1 Announce Type: new Abstract: We introduce PlainMedScale, a topic-aligned medical corpus spanning four levels of comprehensibility in German and English, drawn from MSD (professional

PlantRig - From Bones to Branches: Adaptation of Autoregressive Rigging Models for Plant Skeletal Reconstruction

arXiv:2608.01072v1 Announce Type: new Abstract: Autoregressive rigging models such as UniRig and SkinTokens perform well on articulated characters, but their ability to generalize to plant structures

safetyarxiv-cs-cv

Plasticity of Growing and Elastic Neural Networks in Online Continual Learning

arXiv:2608.01475v1 Announce Type: new Abstract: Neural networks that can grow or both grow and shrink during learning, referred to as growing neural networks and elastic neural networks, respectively,

tutorialsarxiv-cs-lg

PNEC-Mamba: Prototype-Guided Positive-Negative Evidence Calibration for Hyperspectral Image Classification

model-releasesarxiv-cs-cv

arXiv:2608.01910v1 Announce Type: new Abstract: In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local contex

Policy Optimality Measurement for Multi-Vehicle Decision-Making: From Extrinsic Indicators to Intrinsic Quality

arXiv:2608.01133v1 Announce Type: new Abstract: Evaluating Multi-Agent Reinforcement Learning (MARL) policies in autonomous driving fundamentally relies on extrinsic statistical indicators (e.g., rewa

safetyarxiv-cs-lg

Polyatomic Complexes: A topologically-informed learning representation for atomistic systems

arXiv:2409.15600v3 Announce Type: replace Abstract: A representation of a molecule or material should be invariant to the symmetries of physics, unique, continuous, efficient and general. These proper

PolymerGPT: Multi-property Optimization with a Decoder-Based GPT Model for Generative Polymer Design

arXiv:2608.01431v1 Announce Type: cross Abstract: Polymer property prediction and inverse generative design targeting desired properties are two crucial tasks in machine learning-assisted polymer desi

Poplar: A Scalable Pipeline for Human-Centric Image Dataset Synthesis

arXiv:2608.00440v1 Announce Type: new Abstract: Recent image generators can synthesize convincing human-centric images, yet producing a useful collection remains different from producing a single succ

Practical Noise Modeling for SPAD Intensity Imaging

arXiv:2608.00489v1 Announce Type: new Abstract: Single-photon avalanche diode (SPAD) cameras are promising for low-light and high-dynamic-range intensity imaging, but their practical use is limited by

safetyarxiv-cs-cv

Practical Online KV Cache Compaction for LLM Agents: An Empirical Study

arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV c

agentsarxiv-cs-cl

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

model-releasesarxiv-cs-cl

arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains

Predicting Startup Exit from Textual Descriptors - A Computational Linguistics Framework

arXiv:2608.00045v1 Announce Type: new Abstract: This study shows that textual descriptors alone can predict early-stage startup success, defined as Exit, without relying on contextual, financial, or h

Predictive Maintenance: Deep Learning-Based Remaining Useful Life Prediction for Combat Aircraft Engines

arXiv:2608.01819v1 Announce Type: new Abstract: To improve the operational readiness of combat aircraft engines and reduce unplanned maintenance costs, accurately estimating the remaining useful life

Pretrain on Small Synthetic Data, Scale Large for Free: Symmetry-Aware Foundation Model for Logic Rule Induction

arXiv:2608.00383v1 Announce Type: cross Abstract: Logical rule induction seeks interpretable rules that transfer across propositional schemas. This requires respecting symmetries: atom naming, example

Pretraining on Call Graphs: When Binary Analysis Tasks Profit From Context

arXiv:2608.02084v1 Announce Type: cross Abstract: Binary function embedding models are trained to encode the semantics of binary code in such a way that they can be generalized to a variety of reverse

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning

arXiv:2608.01201v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E AD) systems integrate perception, prediction, and planning into a single differentiable architecture. While these m

agentsarxiv-cs-cv

Private Generative Bootstrap via Blocking

model-releasesarxiv-cs-lg

arXiv:2608.02480v1 Announce Type: cross Abstract: With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally import

Probabilistic Deep Learning for Drought Forecasting: Role of Internal Climate Variability

arXiv:2608.01864v1 Announce Type: cross Abstract: Predicting drought risk is essential for anticipating impacts on water resources, agriculture, ecosystems, and climate adaptation planning. Yet drough

Probabilistic Reachable-Action Verification of Visuomotor Policies via Set-Based Training

arXiv:2608.02545v1 Announce Type: new Abstract: Reachability analysis for visuomotor policies is difficult because large visual encoders make end-to-end set propagation computationally expensive and e

safetyarxiv-cs-ro

Probably the best way to run DS4 flash on a mac right now (192gb+ vram)

model-releasesr-localllama

Found this quant, so thought I would share, since its the best I've found so far for running on my mac (m3 ultra). It's got dspark/mtp support so runs faster than anything else I've tried. The tok/s o

Probing the 3D Object-Level Understanding of Pre-Trained Detection Transformers

arXiv:2608.01495v1 Announce Type: new Abstract: Detection transformer models, including DETR and its extensions, learn to output a set of object-level embeddings that can be simultaneously decoded int

tutorialsarxiv-cs-cv

Progressive Agent Skill Generation via Reinforcement Learning

arXiv:2608.01678v1 Announce Type: cross Abstract: Existing skill generation methods largely rely on heuristics or pipeline-style consolidation, which must be specially designed for different evidence

agentsarxiv-cs-cl

Progressive^2: A Teacher-Student Progressive Co-Evolving Knowledge Distillation Method for Substantial Model Compression

arXiv:2608.00129v1 Announce Type: new Abstract: Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student).

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection

arXiv:2608.01348v1 Announce Type: new Abstract: Data augmentation, which simulates diverse visual variations to expand the source distribution and induce synthetic domain shifts, is a simple yet effec

Prompt-Induced Waste in Large Reasoning Models: A Preregistered Two-Harness Benchmark of Coding Agents

model-releasesarxiv-cs-cl

arXiv:2608.01347v1 Announce Type: new Abstract: Large reasoning models used as coding agents incur costs from deliberation, tool calls, and repeated agent turns, yet the causal effect of prompt wordin

PromptPath: Prompt-Adaptive Computational Pathways for In-Context Learning

arXiv:2608.02129v1 Announce Type: new Abstract: In-context learning (ICL) has attracted increasing attention for enabling models to perform new tasks using only a few ``input--output'' prompt examples

Proteus: A Truncation-Robust Entropy Model for Progressive LiDAR Compression

arXiv:2608.00687v1 Announce Type: new Abstract: LiDAR point clouds provide explicit, deterministic physical boundaries critical for collaborative safety-critical perception. However, wireless channels

safetyarxiv-cs-cv

ProtoAct: Turning Wet-Lab Protocols into Embodied Robotic Actions

arXiv:2608.01690v1 Announce Type: new Abstract: Biological wet-lab protocols are written for trained researchers and often leave routine operations, state-dependent conditions, and contextual paramete

researcharxiv-cs-ro

Protocol generalisation for brain tissue microstructure estimation via hypernetwork-controlled geometric deep learning

model-releasesarxiv-cs-cv

arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear

Provably Safe Generative Sampling with Constricting Barrier Functions

arXiv:2602.21429v3 Announce Type: replace Abstract: Flow-based generative models, such as diffusion models and flow matching models, have achieved remarkable success in learning complex data distribut

safetyarxiv-cs-lg

Proxy Avatar Meets Low-Rank Caching: Real-Time One-Shot Emotion-Controllable Portrait Animation

arXiv:2608.01978v1 Announce Type: new Abstract: Audio-driven portrait animation has advanced rapidly with diffusion-based generative models, yet real-time one-shot generation with expressive emotion c

Pruned BPE: Post-training Visibility Pruning and Token Reallocation for Byte Pair Encoding

arXiv:2608.00837v1 Announce Type: new Abstract: Byte Pair Encoding (BPE) is widely used for subword tokenization, but standard BPE exposes every learned merge token to the downstream model, including