11 citations · 19 across the 6 of their papers we have counts for
6 papers
HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models
Haoran Que, Feiyu Duan, Liqun He +11
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks (e.g., long-context understanding), and many benchmarks have been proposed.…
ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code Search
Zehan Li, Jianfei Zhang, Chuantao Yin +2
Retrieval-based code question answering seeks to match user queries in natural language to relevant code snippets. Previous approaches typically rely on pretraining models using cr…
A Review of Data Mining in Personalized Education: Current Trends and Future Prospects
Zhang Xiong, Haoxuan Li, Zhuang Liu +4
Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness…
Discovering Sounding Objects by Audio Queries for Audio Visual Segmentation
Shaofei Huang, Han Li, Yuqing Wang +5
Audio visual segmentation (AVS) aims to segment the sounding objects for each frame of a given video. To distinguish the sounding objects from silent ones, both audio-visual semant…
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
Keheng Wang, Feiyu Duan, Sirui Wang +5
Equipped with Chain-of-Thought (CoT), Large language models (LLMs) have shown impressive reasoning ability in various downstream tasks. Even so, suffering from hallucinations and t…
Evaluating Open-Domain Dialogues in Latent Space with Next Sentence Prediction and Mutual Information
Kun Zhao, Bohao Yang, Chenghua Lin +3
The long-standing one-to-many issue of the open-domain dialogues poses significant challenges for automatic evaluation methods, i.e., there may be multiple suitable responses which…