All Articles
16750 articles total
Field-Aware RankMixer with Dual-Stream Bilinear Fusion for the Tencent UNI-REC Challenge
The authors present FA-RankMixer, a model for multi-domain user behavior sequence modeling for ad pCVR prediction, ranking ninth in the Tencent UNI-REC Challenge.
Scalable LLM Agent Tool Access in the Cloud
A cloud-scale gateway system is proposed for the Model Context Protocol (MCP) to solve tool selection latency and scalability issues for LLM agents.
Process Reward Informed Tree Rollout for Effective Multi-Turn RL
PATR is a rollout framework for multi-turn agent RL that uses process-guided tree rollouts to improve exploration efficiency on benchmarks like SWE-Bench.
AEGIS: Assay-Aware Protocol Validation and Runtime Monitoring for Open-Source Liquid Handling Robots
AEGIS is an open-source system that provides assay-aware protocol validation and visual runtime monitoring for liquid handling robots like the Opentrons OT-2.
Think at 5 Hz, Act at 20 Hz: Asynchronous Fast-Slow Vision-Language-Action Inference for Closed-Loop Driving
A fast-slow architecture for closed-loop driving is introduced, decoupling low-frequency scene reasoning from high-frequency action execution to reduce latency.
A cubical formalisation of topos causal models: intervention, sheaf gluing, and the intuitionistic do-calculus
A machine-checked formalisation of topos causal models is implemented in Cubical Agda, providing a verified account of intervention and sheaf gluing.
IMBench: A Benchmark for Intuitive Robotic Manipulation
IMBench is a new benchmark designed to evaluate the integrated physical reasoning and motor control capabilities of intuitive robotic manipulation.
Sealed Tomb Filled with Paintings and Inscriptions Discovered in Egypt
Discovery of a sealed tomb containing paintings and inscriptions in Egypt.
How proprietary formats have become Microsoft’s main tool for lock-in
An analysis of how Microsoft uses proprietary file formats as a mechanism for vendor lock-in.
Cache-Aware Prompt Compression:A Two-Tier Cost Model for LLM API Caching
Introduces Cache-Aware Prompt Compression (CAPC) to optimize LLM API costs by balancing prompt caching and compression strategies.
SLAPBench: Benchmarking Multimodal Large Language Models for Four-Finger SLAP Fingerprint Verification
Presents SLAPBench, a benchmark for evaluating Multimodal LLMs on four-finger SLAP fingerprint verification.
Recursive Harness Self-Improvement
Introduces Recursive Harness Self-Improvement (RHI) to optimize agent loops and improve execution-trace quality for model training.
Kolmogorov--Arnold Networks for Small Language Models
Evaluates Kolmogorov-Arnold Networks (KANs) as potential replacements for MLPs in small language models, finding limited advantage over strong baselines.
CoWeaver: A Bi-directional, Learnable and Explainable Matching Engine for Mixed Human-Agent Science Collaboration
Proposes CoWeaver, a learnable matching engine designed to facilitate collaboration between human scientists and AI agents.
From Feasibility to Desirability: Plan, Learn, Adapt (PLA) Framework for Personalized On-Device Itinerary Generation
Presents the PLA framework for personalized on-device itinerary generation, combining lightweight planners and a Bradley-Terry reward model.
Evolutionary Algorithm-Guided LLMs for Physics-Informed Neural Network Design
Develops a closed-loop evolutionary algorithm that guides LLMs to design optimal configurations for Physics-Informed Neural Networks (PINNs).
Hard Rules, Soft Preferences: Bridging Reasoning, Learning, and Optimization for Personalized Packing Checklist Generation
Introduces a reasoning-guided learning framework for personalized packing checklists using a symbolic engine and CP-SAT optimizer.
Self-Powered Trailers Promise Leaner Freight Runs
Article discussing self-powered trailers designed to reduce fuel consumption and emissions in freight transport.
Xiaomi-Robotics-1
Discussion regarding Xiaomi's robotics initiatives.
Partial Information Decomposition as a Multi-Contrast 3D MRI Selection Strategy for Resource-Constrained Deep Neural Network Training in Brain Tumor Segmentation
A study on using Partial Information Decomposition to select the most informative MRI input pairs for efficient brain tumor segmentation in deep learning.