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1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Scientific Discovery under Validation Congestion via Multi-Fidelity Pairwise Rankings
Oct 1, 2026Kevin Tirta Wijaya, Alston Lo, Michael Sun +2Drug Discovery Scientific Discovery
University of Bonn · Fraunhofer SCAI · Massachusetts Institute of Technology
Integrating Traffic Noise Emission Modelling into Variable Speed Limit Control
Sep 1, 2026Jiawen Meng, John Pravin Arockiasamy, Alexey VinelStandard Traffic Speed Benchmarks Traffic
Institute AIFB, Karlsruhe Institute of Technology, Germany · School of Information Technology, Halmstad University, Sweden
Interpretable Machine Learning for Traffic Congestion Prediction: Unveiling the Impact of Different COVID-19 Periods
Aug 2, 2026Dan Zhu, Chi Sin Ng, Litian Xie +1Accurate Traffic Forecasting Covid-19
Department of Civil and Environmental Engineering, National University of Singapore, Singapore · Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore
AlphaRoute: Large Language Models as Semantic Optimizers for Multi-Objective Routing
Jul 22, 2026Kabir Murjani, Mishri Bhavsar, Manish I. Patel +1Vehicle Routing Problem Large Language Model Routing
Department of Electrical Engineering, Institute of Technology, Nirma University, Ahmedabad, India · Department of Electronics and Communication Engineering, Institute of Technology, Nirma University, Ahmedabad, India · Center for Semiconductor Microelectronics, Arizona State University, Tempe, Arizona, USA
CLDRoute: Conditional Latent Diffusion for Routability Map Generation in Physical Design
Jul 18, 2026Kiran Thorat, Nicole Meng, Caiwen Ding +2Road Networks Identity-Conditioned Latent Diffusion Models
University of Connecticut · Tufts University · University of Minnesota Twin Cities
Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids
Jul 17, 2026Josef Hoppe, Sarra Bouchkati, Farah Nasr +7Congestion Reinforcement Learning Control
Computational Network Science, RWTH Aachen University · IAEW, RWTH Aachen University · E.ON impulse GmbH +2
HiLLTS: Zero-Shot Hierarchical LLM-Guided Traffic Signal Control for Sustainable Transportation
Jul 17, 2026Yue Ding, Tendai Mukande, Mingming LiuTraffic Signal Control Congestion
Research Ireland Centre for Researching Training in Machine Learning at Dublin City University
Supervised Fine-Tuning vs. In-Context Learning: An Equilibrium Analysis of LLM Personalization under Congestion
Jul 15, 2026Fengzhuo Zhang, Zhuoran Yang, Dirk BergemannLarge Language Model Personalization Personalization
Yale University, 30 Hillhouse Ave., New Haven, CT 06520, USA
Congestion-Based Slot Pricing in a Railway Auction Game
Jul 2, 2026Bill Roungas, Sebastiaan MeijerCongestion Strategic Agents
Panteion University, Athens, Greece · Institute of Communication and Computer Systems, Athens, Greece · KTH Royal Institute of Technology, Stockholm, Sweden
Public transit gains and spatially uneven travel demand changes after NYC congestion pricing
Jun 16, 2026Donghang Li, Dingyi Zhuang, Yunlin Li +5Urban Mobility Congestion
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA · Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA · Center for Computational Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA +4
Service-Induced Congestion in Memory-Constrained LLM Serving
Jun 14, 2026Ruicheng Ao, Jing Dong, Gan Luo +1Large Language Model Serving Large Language Model Memory
Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA 02139 · Columbia Business School, Columbia University, New York, NY 10027 · School of Mathematical Sciences, Peking University, Beijing, China
The Price of Anarchy in Disaggregated Inference
Jun 11, 2026Athos GeorgiouCongestion Prices
NCA
Active Inference for Adaptive Traffic Signal Control in Noisy Nonstationary IoT Environments
May 31, 2026Dénes Toth, George Ambroladze, Edwin Sundberg +2Traffic Signal Control Congestion
Department of Computer Systems and Sciences, Stockholm University, Stockholm 164 25, Sweden
Airport Terminal Passenger Queue Forecasting for Departure Gates and Security Checkpoints
May 30, 2026Juhwan Lee, Seokbin Yoon, Keumjin Lee +2Air Traffic Control Congestion
Department of Air Transport, Transportation, and Logistics, Korea Aerospace University, Goyang, South Korea · Airport Industry Technology Research Institute, Incheon International Airport Corporation, Incheon, South Korea
Kernel-based potential mean-field games with unbiased random Fourier $U$ -statistics
May 28, 2026Yumiharu NakanoMean Field Games Maximum Mean Discrepancy
Department of Mathematical and Computing Science, Institute of Science Tokyo
SpinFlow: A Physics-Informed Spin Field Framework for Traffic Phase Inference and Transition Detection
May 22, 2026Haopeng Deng, Fucheng Zheng, Xinhai XiaTraffic Congestion
School of Future Transportation, Guangzhou Maritime University, Guangzhou, China
CCLab: Adversarial Testing of Learning- and Non-Learning-Based Congestion Controllers
May 21, 2026Zhi Chen, Shehab Sarar Ahmed, Chenkai Wang +2Congestion
UIUC · UIUC & BUET
STEAM: A Training-Free Congestion-Aware Enhancement Framework for Decentralized Multi-Agent Path Finding
May 20, 2026Mingyang Feng, Mengnuo Zhang, Shaoyuan Li +1Multi-Agent Path Finding Decentralized Learning
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China
Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention
May 13, 2026Yuanzhe Wang, Tian Zhi, Zihang Wei +8Multi-Agent Path Finding Diffusion Planning
State Key Lab of Processors, Institute of Computing Technology, CAS · School of Advanced Interdisciplinary Sciences, CAS · University of Chinese Academy of Sciences +1
An Integrated Forecasting Prototype for Emergency Department Boarding Time to Support Proactive Operational Decision Making
May 13, 2026Orhun Vural, Abdulaziz Ahmed, Ferhat Zengul +2Readmission Prediction Emergency Departments
Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA · Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, AL, USA · Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA +1
Token Economics for LLM Agents: A Dual-View Study from Computing and Economics
May 9, 2026Yuxi Chen, Junming Chen, Chenyu He +9Economies Large Language Model Agents
College of Computer Science and Technology, Zhejiang University · School of Economics, Zhejiang University · The State Key Laboratory of Blockchain and Data Security, Zhejiang University +1
Anchor-and-Resume Concession Under Dynamic Pricing for LLM-Augmented Freight Negotiation
Apr 22, 2026Hoang Nguyen, Lu Wang, Marta Gaia BrasDynamic Pricing Negotiation
Georgia Institute of Technology · Atlanta, Georgia, USA · Transportation Insight / NTG
Toward Non-Expert Customized Congestion Control: Large Language Model-Assisted CCA Code Generation with eBPF Deployment
Jan 30, 2026Mingrui Zhang, Hamid Bagheri, Lisong XuCongestion Semantic Firewall
School of Computing, University of Nebraska-Lincoln

Oct 1, 2026, cs.LGJ/K move · Enter open · S save

Scientific Discovery under Validation Congestion via Multi-Fidelity Pairwise Rankings

Kevin Tirta Wijaya, Alston Lo, Michael Sun, Wojciech Matusik+1

University of Bonn · Fraunhofer SCAI · Massachusetts Institute of Technology

Drug Discovery Scientific Discovery Screening Data-Curation Validation Congestion

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Modern computational methods can now propose candidate molecules, materials, and other scientific designs at an unprecedented scale, creating a validation congestion where candidates are abundant, but experimental capacity to physically evaluate them remains scarce. Discovering novel scientific designs has therefore become increasingly dependent on curation: selecting a small set of promising designs for slow and costly experiments. Existing curation methods typically rely on data-driven regression models that predict absolute scores, but training these models requires substantial experimental data to begin with. Yet, useful curation signals do not have to take the form of absolute measurements, as scientific design discovery is often comparative in nature. Here, we propose that curation can instead be primarily driven by expert pairwise rankings, which are substantially easier to gather. The expertise can come from computational tools or human input of multiple levels of fidelity, ranging from empirical rules of thumb to agentic workflows and experienced scientists. We introduce PRISMS, a framework that uses pairwise rankings from one or more experts, potentially spanning multiple levels of expertise, to identify the most promising candidates without relying on data-hungry regressors. When experts differ in fidelity and cost, PRISMS escalates pairwise queries from lower- to higher-fidelity rankers based on a Fisher-information criterion. In iterative screening that selects designs from fixed drug discovery libraries, PRISMS achieves 50% top-10 discovery recall in ~42% fewer rounds than regression-only active learning, and in ~15% fewer rounds than the ranking-based method with no selective escalation. In optimization that generates new designs without restriction to a predefined library, PRISMS achieves ~18.8% higher hypervolume than the Bayesian optimization baseline.

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