most citedAutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

DeepSearchQA: Bridging the Comprehensiveness Gap for Deep Research Agents

Nikita Gupta, Riju Chatterjee, Lukas Haas +9

We introduce DeepSearchQA, a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional benchmarks…

cs.CL2026

Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction

Shuoxin Wang, Chang Liu, Gowen Loo +5

Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking perso…

cs.CL2025

SCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema

Yushen Fang, Jianjun Li, Mingqian Ding +3

Although Large language Model (LLM)-powered information extraction (IE) systems have shown impressive capabilities, current fine-tuning paradigms face two major limitations: high t…

cs.CL2025

POLIS-Bench: Towards Multi-Dimensional Evaluation of LLMs for Bilingual Policy Tasks in Governmental Scenarios

Tingyue Yang, Junchi Yao, Yuhui Guo +1

We introduce POLIS-Bench, the first rigorous, systematic evaluation suite designed for LLMs operating in governmental bilingual policy scenarios. Compared to existing benchmarks, P…

cs.LG2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…

cs.SE20251 cited

AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine

Shuyang Hou, Zhangxiao Shen, Huayi Wu +10

Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task…