9 citations · 17 across the 6 of their papers we have counts for
6 papers
RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data
Zhengkang Guo, Wenhao Liu, Mingchen Xie +13
Large language models (LLMs) are increasingly expected to tackle complex tasks, driven by their expanding applications and users' growing proficiency in crafting sophisticated prom…
LLaMA Beyond English: An Empirical Study on Language Capability Transfer
Jun Zhao, Zhihao Zhang, Luhui Gao +3
In recent times, substantial advancements have been witnessed in large language models (LLMs), exemplified by ChatGPT, showcasing remarkable proficiency across a range of complex t…
RoTBench: A Multi-Level Benchmark for Evaluating the Robustness of Large Language Models in Tool Learning
Junjie Ye, Yilong Wu, Songyang Gao +7
Tool learning has generated widespread interest as a vital means of interaction between Large Language Models (LLMs) and the physical world. Current research predominantly emphasiz…
ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios
Junjie Ye, Guanyu Li, Songyang Gao +9
Existing evaluations of tool learning primarily focus on validating the alignment of selected tools for large language models (LLMs) with expected outcomes. However, these approach…
SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network
Changze Lv, Tianlong Li, Wenhao Liu +6
Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs), demonstrating comparable performance in both visual and li…
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing
Tao Gui, Xiao Wang, Qi Zhang +31
Various robustness evaluation methodologies from different perspectives have been proposed for different natural language processing (NLP) tasks. These methods have often focused o…