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Yebowen Hu

7 accepted papers

2025

DeFine: Decision-Making with Analogical Reasoning over Factor Profiles

ACL 2025finding

LLMs are ideal for decision-making thanks to their ability to reason over long contexts. However, challenges arise when processing speech transcripts that describe complex scenarios, as they are verbose and include repetition, hedging, and vagueness. E.g., during a company’s earnings call, an execut…

Cited by 0SourcePDFScholar
2025

STRUX: An LLM for Decision-Making with Structured Explanations

NAACL 2025short

Countless decisions shape our lives, and it is crucial to understand the how and why behind them. In this paper, we introduce a new LLM decision-making framework called STRUX, which enhances LLM decision-making by providing structured explanations. These include favorable and adverse facts related t…

Cited by 2SourcePDFScholar
2024

InFoBench: Evaluating Instruction Following Ability in Large Language Models

ACL 2024findings

This paper introduces the Decomposed Requirements Following Ratio (DRFR), a new metric for evaluating Large Language Models’ (LLMs) ability to follow instructions. Addressing a gap in current methodologies, DRFR breaks down complex instructions into simpler criteria, facilitating a detailed analysis…

2024

SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs

ACL 2024long

Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and numerical data presents substantial challenges. LLMs need to process and cross-reference entities and numbers, handle d…

Cited by 8SourcePDFScholar
2024

When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives

EMNLP 2024main

Reasoning is most powerful when an LLM accurately aggregates relevant information. We examine the critical role of information aggregation in reasoning by requiring the LLM to analyze sports narratives. To succeed at this task, an LLM must infer points from actions, identify related entities, attrib…

2023

DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4

EMNLP 2023long main

Human preference judgments are pivotal in guiding large language models (LLMs) to produce outputs that align with human values. Human evaluations are also used in summarization tasks to compare outputs from various systems, complementing existing automatic metrics. Despite their significance, howeve…

Cited by 0SourceScholar
2023

MeetingBank: A Benchmark Dataset for Meeting Summarization

ACL 2023long

As the number of recorded meetings increases, it becomes increasingly important to utilize summarization technology to create useful summaries of these recordings. However, there is a crucial lack of annotated meeting corpora for developing this technology, as it can be hard to collect meetings, esp…