9 citations · 11 across the 9 of their papers we have counts for
9 papers
CCR-Bench: A Comprehensive Benchmark for Evaluating LLMs on Complex Constraints, Control Flows, and Real-World Cases
Xiaona Xue, Yiqiao Huang, Jiacheng Li +9
Enhancing the ability of large language models (LLMs) to follow complex instructions is critical for their deployment in real-world applications. However, existing evaluation metho…
Beyond Quality: Unlocking Diversity in Ad Headline Generation with Large Language Models
Chang Wang, Siyu Yan, Depeng Yuan +8
The generation of ad headlines plays a vital role in modern advertising, where both quality and diversity are essential to engage a broad range of audience segments. Current approa…
How Good are LLMs at Relation Extraction under Low-Resource Scenario? Comprehensive Evaluation
Dawulie Jinensibieke, Mieradilijiang Maimaiti, Wentao Xiao +2
Relation Extraction (RE) serves as a crucial technology for transforming unstructured text into structured information, especially within the framework of Knowledge Graph developme…
ToolRerank: Adaptive and Hierarchy-Aware Reranking for Tool Retrieval
Yuanhang Zheng, Peng Li, Wei Liu +3
Tool learning aims to extend the capabilities of large language models (LLMs) with external tools. A major challenge in tool learning is how to support a large number of tools, inc…
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching
Mieradilijiang Maimaiti, Yuanhang Zheng, Ji Zhang +3
Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-cus…
Budget-Constrained Tool Learning with Planning
Yuanhang Zheng, Peng Li, Ming Yan +3
Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, ha…