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Hayate Iso

7 accepted papers

2025

Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education

NAACL 2025industry

Large Language Models (LLMs) offer the potential to automate hiring by matching job descriptions with candidate resumes, streamlining recruitment processes, and reducing operational costs. However, biases inherent in these models may lead to unfair hiring practices, reinforcing societal prejudices a…

2025

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization

NAACL 2025findings

Although many studies have investigated and reduced hallucinations in large language models (LLMs) for single-document tasks, research on hallucination in multi-document summarization (MDS) tasks remains largely unexplored. Specifically, it is unclear how the challenges arising from handling multipl…

2025

Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data

ICLR 2025poster

The rapid increase in textual information means we need more efficient methods to sift through, organize, and understand it all. While retrieval-augmented generation (RAG) models excel in accessing information from large document collections, they struggle with complex tasks that require aggregation…

Cited by 1SourcePDFScholar
2024

Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models

NAACL 2024long

While large language models (LMs) demonstrate remarkable performance, they encounter challenges in providing accurate responses when queried for information beyond their pre-trained memorization. Although augmenting them with relevant external information can mitigate these issues, failure to consid…

2024

XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates

COLING 2024main

Text editing is a crucial task of modifying text to better align with user intents. However, existing text editing benchmark datasets contain only coarse-grained instructions and lack explainability, thus resulting in outputs that deviate from the intended changes outlined in the gold reference. To…

2022

Comparative Opinion Summarization via Collaborative Decoding

ACL 2022findings

Opinion summarization focuses on generating summaries that reflect popular subjective information expressed in multiple online reviews. While generated summaries offer general and concise information about a particular hotel or product, the information may be insufficient to help the user compare mu…

2021

Convex Aggregation for Opinion Summarization

EMNLP 2021finding

Recent advances in text autoencoders have significantly improved the quality of the latent space, which enables models to generate grammatical and consistent text from aggregated latent vectors. As a successful application of this property, unsupervised opinion summarization models generate a summar…