7 papers
PLoRA: An NDP-Enhanced Pooled-Memory System for Cost-Efficient Multi-LoRA Serving
Zhongkai Yu, Ohm Rishabh Venkatachalam, Zheng Wang +9
Multi-LoRA serving is how one base model becomes thousands of specialized variants, one adapter per user, task, or agent, and the deployments can hold 1000-plus adapters. Serving t…
Evolutionary Physics-Informed Temporal Fusion for Lane-Change Intention Prediction
Jiazhao Shi, Qiyang Xie, Ziyu Wang +7
Early lane-change intention prediction is essential for autonomous driving and ADAS, but it remains challenging because lane-changing behavior depends on evolving traffic risk, sur…
ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation
Zhongkai Yu, Yichen Lin, Chenyang Zhou +12
Existing API-based agentic systems for RTL code generation are fundamentally misaligned with industrial practice: they assume a golden testbench is available at generation time, re…
ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design
Zhongkai Yu, Chenyang Zhou, Yichen Lin +6
While Large Language Models (LLMs) show significant potential in hardware engineering, current benchmarks suffer from saturation and limited task diversity, failing to reflect LLMs…
Multi-Scenario Highway Lane-Change Intention Prediction: A Physics-Informed AI Framework for Three-Class Classification
Jiazhao Shi, Yichen Lin, Yiheng Hua +6
Lane-change maneuvers are a leading cause of highway accidents, underscoring the need for accurate intention prediction to improve the safety and decision-making of autonomous driv…
Towards Physics-informed Spatial Intelligence with Human Priors: An Autonomous Driving Pilot Study
Guanlin Wu, Boyan Su, Yang Zhao +3
How to integrate and verify spatial intelligence in foundation models remains an open challenge. Current practice often proxies Visual-Spatial Intelligence (VSI) with purely textua…