activity
20182025
most citedEfficient Attentions for Long Document Summarization

11 citations · 17 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CL2025

ExpertLongBench: Benchmarking Language Models on Expert-Level Long-Form Generation Tasks with Structured Checklists

Jie Ruan, Inderjeet Nair, Shuyang Cao +14

This paper introduces ExpertLongBench, an expert-level benchmark containing 11 tasks from 9 domains that reflect realistic expert workflows and applications. Beyond question answer…

cs.CL20251 cited

Evaluating the Retrieval Robustness of Large Language Models

Shuyang Cao, Karthik Radhakrishnan, David Rosenberg +4

Retrieval-augmented generation (RAG) generally enhances large language models' (LLMs) ability to solve knowledge-intensive tasks. But RAG may also lead to performance degradation d…

cs.CL2022

Time-aware Prompting for Text Generation

Shuyang Cao, Lu Wang

In this paper, we study the effects of incorporating timestamps, such as document creation dates, into generation systems. Two types of time-aware prompts are investigated: (1) tex…

cs.CL2022

HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization

Shuyang Cao, Lu Wang

Document structure is critical for efficient information consumption. However, it is challenging to encode it efficiently into the modern Transformer architecture. In this work, we…

cs.CL2021

CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization

Shuyang Cao, Lu Wang

We study generating abstractive summaries that are faithful and factually consistent with the given articles. A novel contrastive learning formulation is presented, which leverages…

cs.CL20212 cited

Controllable Open-ended Question Generation with A New Question Type Ontology

Shuyang Cao, Lu Wang

We investigate the less-explored task of generating open-ended questions that are typically answered by multiple sentences. We first define a new question type ontology which diffe…