6 citations · 10 across the 6 of their papers we have counts for
6 papers
Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression
Xinze Li, Zhenghao Liu, Chenyan Xiong +4
Large language models (LLMs) require lengthy prompts as the input context to produce output aligned with user intentions, a process that incurs extra costs during inference. In thi…
CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network
Yumeng Song, Yu Gu, Tianyi Li +4
Hypergraphs can model higher-order relationships among data objects that are found in applications such as social networks and bioinformatics. However, recent studies on hypergraph…
Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval
Zhenghao Liu, Chenyan Xiong, Yuanhuiyi Lv +2
This paper presents Universal Vision-Language Dense Retrieval (UniVL-DR), which builds a unified model for multi-modal retrieval. UniVL-DR encodes queries and multi-modality resour…
TIAGE: A Benchmark for Topic-Shift Aware Dialog Modeling
Huiyuan Xie, Zhenghao Liu, Chenyan Xiong +2
Human conversations naturally evolve around different topics and fluently move between them. In research on dialog systems, the ability to actively and smoothly transition to new t…
Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision
Si Sun, Yingzhuo Qian, Zhenghao Liu +5
The effectiveness of Neural Information Retrieval (Neu-IR) often depends on a large scale of in-domain relevance training signals, which are not always available in real-world rank…
Capturing Global Informativeness in Open Domain Keyphrase Extraction
Si Sun, Zhenghao Liu, Chenyan Xiong +2
Open-domain KeyPhrase Extraction (KPE) aims to extract keyphrases from documents without domain or quality restrictions, e.g., web pages with variant domains and qualities. Recentl…