17 citations · 17 across the 4 of their papers we have counts for
4 papers
DoPR: Reusable Compressed Document Prefixes for Efficient LLM Reranking
Beiya Dai, Yifan Wei, Guang Yang +3
Large language models (LLMs) are effective rerankers, but pointwise reranking repeatedly processes the same document across different queries, causing substantial redundant documen…
Context-level Language Modeling by Learning Predictive Context Embeddings
Beiya Dai, Yuliang Liu, Daozheng Xue +6
We propose ContextLM, a framework that implicitly learns multi-token prediction by augmenting standard pretraining with an intrinsic next-context prediction objective. ContextLM bu…
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning
Peng Yu, Cheng Deng, Beiya Dai +2
Autoregressive large language models (LLMs) pre-trained by next token prediction are inherently proficient in generative tasks. However, their performance on knowledge-driven tasks…
GeoGalactica: A Scientific Large Language Model in Geoscience
Zhouhan Lin, Cheng Deng, Le Zhou +18
Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their…