most citedCEBench: A Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines

5 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents

Liangtian Liu, Zeyuan Wang, Ziyu Li +8

The rise of multi-modal large language models (MLLMs) is shifting remote sensing (RS) intelligence from "see" to "action", as OpenClaw-style frameworks enable agents to autonomousl…

cs.LG2026

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization

Xu Chu, Guanyu Wang, Zhijie Tan +4

Large Language Models (LLMs) suffer from order bias, where their performance is affected by the arrangement order of input elements. This unfairness limits the model's applications…

cs.IR2024

LLM-PQA: LLM-enhanced Prediction Query Answering

Ziyu Li, Wenjie Zhao, Asterios Katsifodimos +1

The advent of Large Language Models (LLMs) provides an opportunity to change the way queries are processed, moving beyond the constraints of conventional SQL-based database systems…

cs.PF2024★ 5 cited

CEBench: A Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines

Wenbo Sun, Jiaqi Wang, Qiming Guo +3

Online Large Language Model (LLM) services such as ChatGPT and Claude 3 have transformed business operations and academic research by effortlessly enabling new opportunities. Howev…

cs.LG2024

Model Selection with Model Zoo via Graph Learning

Ziyu Li, Hilco van der Wilk, Danning Zhan +3

Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.e., model zoos. Given a new prediction task, finding the best model to fine-tune can be…