10 papers
DF-ReAG: Dynamic Decomposition and Filtering for Multi-Hop Reasoning-Augmented Generation
Jiaoyang Li, Junhao Ruan, Shengwei Tang +4
Large language models (LLMs) often generate inaccurate answers due to their reliance on static internal knowledge. Retrieval-augmented generation (RAG) addresses this limitation by…
Stress-Relief Annealing: Polynomial-Time Simulation-Free Layout Optimization for Automated Warehouses
Xiangjie Luo, Yulun Zhang, Miyuki Koshimura +2
We study the problem of optimizing physical layouts for automated warehouses, where hundreds to thousands of robots are coordinated to transport packages. Previous works have shown…
MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation
Yutong Wang, Pengliang Ji, Chaoqun Yang +4
The LLM-as-a-Judge paradigm shows promise for evaluating generative content but lacks reliability in reasoning-intensive scenarios, such as programming. Inspired by recent advances…
QD-MAPPER: A Quality Diversity Framework to Automatically Evaluate Multi-Agent Path Finding Algorithms in Diverse Maps
Cheng Qian, Yulun Zhang, Varun Bhatt +3
We use the Quality Diversity (QD) algorithm with Neural Cellular Automata (NCA) to automatically evaluate Multi-Agent Path Finding (MAPF) algorithms by generating diverse maps. Pre…
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Chenyang Shao, Dehao Huang, Yu Li +18
With the rapid development of Large Language Models (LLMs), AI agents have demonstrated increasing proficiency in scientific tasks, ranging from hypothesis generation and experimen…
SUBQRAG: Sub-Question Driven Dynamic Graph RAG
Jiaoyang Li, Junhao Ruan, Shengwei Tang +5
Graph Retrieval-Augmented Generation (Graph RAG) effectively builds a knowledge graph (KG) to connect disparate facts across a large document corpus. However, this broad-view appro…