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20182026
most citedRetrieval-Enhanced Machine Learning

51 citations · 172 across the 23 of their papers we have counts for

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14 papers · 1 filter

cs.CL2024

Integrating Planning into Single-Turn Long-Form Text Generation

Yi Liang, You Wu, Honglei Zhuang +8

Generating high-quality, in-depth textual documents, such as academic papers, news articles, Wikipedia entries, and books, remains a significant challenge for Large Language Models…

cs.CL2024

Inference Scaling for Long-Context Retrieval Augmented Generation

Zhenrui Yue, Honglei Zhuang, Aijun Bai +7

The scaling of inference computation has unlocked the potential of long-context large language models (LLMs) across diverse settings. For knowledge-intensive tasks, the increased c…

cs.CL2024

Multilingual Fine-Grained News Headline Hallucination Detection

Jiaming Shen, Tianqi Liu, Jialu Liu +4

The popularity of automated news headline generation has surged with advancements in pre-trained language models. However, these models often suffer from the ``hallucination'' prob…

cs.CL2024

Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generation

Jiaming Shen, Ran Xu, Yennie Jun +6

Reward models (RMs) are crucial for aligning large language models (LLMs) with human preferences. They are trained using preference datasets where each example consists of one inpu…

cs.CL2024

PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs

Rongzhi Zhang, Jiaming Shen, Tianqi Liu +7

Large Language Models (LLMs) have exhibited impressive capabilities in various tasks, yet their vast parameter sizes restrict their applicability in resource-constrained settings.…

cs.CL2023

Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning

Yue Yu, Jiaming Shen, Tianqi Liu +5

Large language models (LLMs) have shown remarkable capabilities in various natural language understanding tasks. With only a few demonstration examples, these LLMs can quickly adap…