Papers by Hassan Foroosh
When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives (2024.emnlp-main)
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| Challenge: | Using sports data, an LLM can analyze sports narratives to infer points from actions, identify related entities, attribute points accurately to players and teams, and draw conclusions. |
| Approach: | They propose a method to synthesize NBA basketball game narratives using real NBA basketball data and propose 'SportsGen' they find that most models fail to accurately aggregate basketball scores due to frequent scoring patterns and open-source models suffer from significant score hallucinations. |
| Outcome: | The proposed method can evaluate LLMs’ reasoning capabilities under complex scenarios with varying narrative lengths and density of information. |
DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4 (2023.emnlp-main)
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| Challenge: | Human preference judgments are important in large language models to produce outputs that align with human values. |
| Approach: | They conduct an in-depth examination of pairwise human judgments released by OpenAI . they find that most favored factors vary across tasks and genres . |
| Outcome: | The proposed model reveals that most favored factors vary across tasks and genres . the findings have implications on the construction of balanced datasets in human preference evaluations - crucial step in shaping behavior of future LLMs. |
DeFine: Decision-Making with Analogical Reasoning over Factor Profiles (2025.findings-acl)
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| Challenge: | Large language models are ideal for decision-making, but they can be difficult to process when they are verbose and include repetition, hedging, and vagueness. |
| Approach: | They propose a framework that constructs probabilistic factor profiles from complex scenarios and integrates them with analogical reasoning to guide LLMs in making decisions in new situations. |
| Outcome: | The proposed framework separates the tasks of quantifying uncertainty and incorporating it into LLM decision-making. |
Better Highlighting: Creating Sub-Sentence Summary Highlights (2020.emnlp-main)
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| Challenge: | Abstractive summarizations are considered to be less reliable because they distort the original meaning and can be confusing for readers. |
| Approach: | They propose a method to generate summary highlights that are understandable on their own to avoid confusion. |
| Outcome: | The proposed method allows summaries to be understood in context and avoids misdirecting readers to false conclusions. |
SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs (2024.acl-long)
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| Challenge: | Large language models can handle text and data, but blending text and numerical data presents significant challenges. |
| Approach: | They propose four tasks to evaluate the numerical reasoning and information fusion capabilities of large language models in sports data analytics. |
| Outcome: | The proposed tasks evaluate the numerical reasoning and information fusion capabilities of large language models in sports data analytics. |
Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations (D19-54)
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| Challenge: | Determinantal point processes (DPP) is one of the best performing techniques for extractive summarization. |
| Approach: | They propose to combine determinantal point processes with surface indicators for effective identification of summary-worthy sentences. |
| Outcome: | The determinantal point processes (DPP) framework is one of the best performing in summarization competitions. |
StreamHover: Livestream Transcript Summarization and Annotation (2021.emnlp-main)
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Sangwoo Cho, Franck Dernoncourt, Tim Ganter, Trung Bui, Nedim Lipka, Walter Chang, Hailin Jin, Jonathan Brandt, Hassan Foroosh, Fei Liu
| Challenge: | StreamHover is a framework for annotating and summarizing livestream transcripts . the problem is that there is n't enough annotated datasets to summarize livestreams based on the informal nature of spoken language . |
| Approach: | They propose a framework for annotating and summarizing livestream transcripts using a text preview. |
| Outcome: | The proposed model generalizes better and improves over strong baselines. |
Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization (P19-1)
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| Challenge: | Despite the empirical success of multi-document summarization, most datasets remain small and the cost of hiring hu-1 is prohibitive. |
| Approach: | They propose a novel method for extractive multi-document summarization that measures redundancy between a pair of sentences based on surface form and semantic information. |
| Outcome: | The proposed method outperforms baseline methods on benchmark datasets and is particularly useful for documents created by multiple authors containing redundant yet lexically diverse expressions. |
STRUX: An LLM for Decision-Making with Structured Explanations (2025.naacl-short)
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| Challenge: | a new LLM decision-making framework is designed to help users understand how and why decisions are made. |
| Approach: | They introduce a new LLM decision-making framework called STRUX that provides structured explanations for LLM decisions. |
| Outcome: | The proposed framework improves decision-making by providing structured explanations . it has been evaluated on the task of forecasting stock investment decisions based on earnings call transcripts - superior performance against strong baselines compared with previous frameworks based upon earnings call transcriptions demonstrating superior performance . |
MeetingBank: A Benchmark Dataset for Meeting Summarization (2023.acl-long)
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| Challenge: | a lack of annotated meeting corpora hinders the development of meeting summarization technology. |
| Approach: | They present a new benchmark dataset of city council meetings over the past decade . they use a divide-and-conquer approach to divide professionally written minutes into shorter passages . |
| Outcome: | The proposed dataset provides a testbed for various meeting summarization systems and allows the public to gain insight into how council decisions are made. |