1 citations · 1 across the 4 of their papers we have counts for
5 papers
CARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generation
Yutong Song, Jiang Wu, Weijia Zhang +7
Adapting large language models to individual users remains challenging due to the tension between fine-grained personalization and scalable deployment. We present CARD, a hierarchi…
Summarize-Exemplify-Reflect: Data-driven Insight Distillation Empowers LLMs for Few-shot Tabular Classification
Yifei Yuan, Jiatong Li, Weijia Zhang +3
Recent studies show the promise of large language models (LLMs) for few-shot tabular classification but highlight challenges due to the variability in structured data. To address t…
Beyond Natural Language Plans: Structure-Aware Planning for Query-Focused Table Summarization
Weijia Zhang, Songgaojun Deng, Evangelos Kanoulas
Query-focused table summarization requires complex reasoning, often approached through step-by-step natural language (NL) plans. However, NL plans are inherently ambiguous and lack…
A Comparative Analysis of Faithfulness Metrics and Humans in Citation Evaluation
Weijia Zhang, Mohammad Aliannejadi, Jiahuan Pei +3
Large language models (LLMs) often generate content with unsupported or unverifiable content, known as "hallucinations." To address this, retrieval-augmented LLMs are employed to i…
Beyond Relevant Documents: A Knowledge-Intensive Approach for Query-Focused Summarization using Large Language Models
Weijia Zhang, Jia-Hong Huang, Svitlana Vakulenko +3
Query-focused summarization (QFS) is a fundamental task in natural language processing with broad applications, including search engines and report generation. However, traditional…