Papers with HTML
Struc-Bench: Are Large Language Models Good at Generating Complex Structured Tabular Data? (2024.naacl-short)
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| Challenge: | Large Language Models (LLMs) have advanced capabilities but produce complex structured data. |
| Approach: | They propose a structure-aware fine-tuning method to bolster LLMs' performance by crafting format-specific instructions from the intended outputs. |
| Outcome: | The proposed method outperforms LLMs on all three formats and spans text tables, HTML, and LaTeX formats. |
Vis-Eval Metric Viewer: A Visualisation Tool for Inspecting and Evaluating Metric Scores of Machine Translation Output (N18-5)
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| Challenge: | Many metrics have been proposed for Machine Translation (MT) that compare system translations against human references. |
| Approach: | They propose to use BLEU and METEOR to evaluate machine translations against human translations. |
| Outcome: | VisEval Metric Viewer (VEMV) provides visualisation of multiple evaluation scores so they can be easily interpreted by a user. |
GATE Teamware 2: An open-source tool for collaborative document classification annotation (2023.eacl-demo)
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| Challenge: | GATE Teamware 2 is an open-source web-based platform for managing teams of annotators working on document classification tasks. |
| Approach: | They present GATE Teamware 2: an open-source web-based platform for managing teams of annotators working on document classification tasks. |
| Outcome: | GATE Teamware 2 is an open-source web-based platform for managing teams of annotators working on document classification tasks. |
Improving Knowledge Base Construction from Robust Infobox Extraction (N19-2)
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| Challenge: | Existing knowledge bases are incomplete, resulting in poor answers and incompleteness. |
| Approach: | They propose a method to extract Wikipedia infobox tables to populate an existing KB. |
| Outcome: | The proposed method improves accuracy and completeness of the final KB significantly compared to DBpedia's baseline method. |
Community lexical access for an endangered polysynthetic language: An electronic dictionary for St. Lawrence Island Yupik (N19-4)
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| Challenge: | a new electronic dictionary for St. Lawrence Island Yupik is developed to facilitate language-learning on the island . the endangered language is spoken primarily on St. lisa's St.liss island, Alaska . |
| Approach: | They propose a morphologically-aware electronic dictionary for St. Lawrence Island Yupik . the dictionary is set in an uncluttered interface and uses HTML, Javascript, and CSS . |
| Outcome: | The proposed dictionary is set in an uncluttered interface and is available in English and in Yupik . it is based on the morphologically-aware version of the Badten et al. paper dictionary . |
Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions (2024.acl-demos)
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| Challenge: | Fundus is a news scraper that extracts news articles from the web with just a few lines of code. |
| Approach: | They introduce Fundus, a news scraper that enables users to obtain news articles with just a few lines of code. |
| Outcome: | The proposed news scraper optimizes for quality and provides a unified interface for newspapers. |
Leveraging HTML in Free Text Web Named Entity Recognition (2020.coling-main)
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| Challenge: | Named Entity Recognition (NER) is the identification of the proper names of objects. |
| Approach: | They compare HTML tags discarded in free text Named Entity Recognition from Web pages . they find an increased F1 performance for Text+Tags of between 0.9% and 13.2% . |
| Outcome: | The proposed method improves F1 performance over datasets, variants and models. |
Paper2Web: Let’s Make Your Paper Alive! (2026.acl-demo)
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| Challenge: | Current approaches to creating layout-aware, interactive academic webpages are limited. |
| Approach: | They propose a benchmark dataset and evaluation framework for assessing academic webpage generation that incorporates rule-based metrics like Connectivity, Completeness and PaperQuiz. |
| Outcome: | The proposed framework outperforms baselines like template-based webpages and arXiv/alphaXivo versions while maintaining low cost. |
Semantic Outlier Removal with Embedding Models and LLMs (2025.acl-industry)
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Eren Akbiyik, João F. M. De Almeida, Rik Melis, Ritu Sriram, Viviana Petrescu, Vilhjálmur Vilhjálmsson
| Challenge: | Modern text processing pipelines require robust methods to remove extraneous content while preserving a document’s core message. |
| Approach: | They propose a method that leverages multilingual sentence embeddings and approximate nearest-neighbor search to identify and excise unwanted text segments. |
| Outcome: | Experiments on HTML datasets show that SORE outperforms structural methods and yields high precision in diverse scenarios. |
Supervised and Unsupervised Methods for Robust Separation of Section Titles and Prose Text in Web Documents (D18-1)
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| Challenge: | a web text structure is underutilized, but its visual organization is useful for NLP tasks . a flexible system for extracting hierarchical section titles and prose organization is developed . |
| Approach: | a new system extracts hierarchical section titles and prose organization from web documents . the system uses features from syntax, semantics, discourse and markup to build two models . |
| Outcome: | a new system extracts the hierarchical section titles and prose organization of web documents . the system achieves an overall precision of 0.82 and a recall of 0.98 on three domains of web text . |
Transc&Anno: A Graphical Tool for the Transcription and On-the-Fly Annotation of Handwritten Documents (L18-1)
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| Challenge: | Transc&Anno is a web-based collaboration tool for linguists to facilitate the transcription of text images and their shallow on-the-fly annotation. |
| Approach: | They propose a web-based collaboration tool that allows the transcription of text images and their shallow on-the-fly annotation. |
| Outcome: | The Transc&Anno tool can be used for any type of corpora requiring transcription and shallow on-the-fly annotation resulting in inline XML. |
A Corpus of Spanish Political Speeches from 1937 to 2019 (2020.lrec-1)
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| Challenge: | a corpus of political speeches in Spanish is documented from 1937 to 2019 . the corpus contains the speeches delivered by the head of state of Spain on Christmas Eve . |
| Approach: | They propose to collect political speeches from the Christmas Eve national speeches from 1937 to 2019 . they propose a Python interface that allows querying and analyzing the corpus . |
| Outcome: | The proposed corpus contains speeches delivered by the king of Spain from 1937 to 2019 . the documents reflect some of the most significant events and political changes in recent history . a set of HTML visualizations is provided to navigate the corpus and explore differences between TF-IDF frequencies. |
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages (2022.naacl-main)
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| Challenge: | Existing models for structural reading comprehension (SRC) only focus on comprehension of plain text, tables, tables or knowledge bases. |
| Approach: | They propose a topological information enhanced model which transforms a token-level task into a tag-level one by introducing a two-stage process. |
| Outcome: | The proposed model outperforms baselines and achieves state-of-the-art performance on the web-based SRC benchmark WebSRC at the time of writing. |
AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation (2024.emnlp-main)
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Wenhao Huang, Zhouhong Gu, Chenghao Peng, Jiaqing Liang, Zhixu Li, Yanghua Xiao, Liqian Wen, Zulong Chen
| Challenge: | Existing methods for web scraping suffer from limited adaptability and scalability when faced with a new website. |
| Approach: | They propose a framework that generates web scrapers with large language models and a new executability metric to measure the performance of web scraper generation tasks. |
| Outcome: | The proposed framework can handle diverse web environments more efficiently. |
Understanding HTML with Large Language Models (2023.findings-emnlp)
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Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust
| Challenge: | Large language models have shown exceptional performance on a variety of natural language tasks, but their capabilities for HTML understanding have not been fully explored. |
| Approach: | They propose to use HTML understanding models to parse HTML and perform HTML navigation tasks with a large-scale HTML dataset. |
| Outcome: | The proposed models perform 50% more tasks with 192x less data than the previous best supervised model. |
TurkingBench: A Challenge Benchmark for Web Agents (2025.naacl-long)
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Kevin Xu, Yeganeh Kordi, Tanay Nayak, Adi Asija, Yizhong Wang, Kate Sanders, Adam Byerly, Jingyu Zhang, Benjamin Van Durme, Daniel Khashabi
| Challenge: | TurkingBench is a benchmark consisting of tasks presented as web pages with textual instructions and multi-modal contexts. |
| Approach: | They propose to use HTML pages to perform various annotation tasks on crowdsourcing platforms. |
| Outcome: | The proposed model outperforms other models on the TurkingBench benchmark. |
Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pre-training (2026.findings-eacl)
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Jeffrey Li, Joshua P Gardner, Doug Kang, Fangping Shi, Karanjeet Singh, Chun-Liang Li, Herumb Shandilya, David Leo Wright Hall, Oncel Tuzel, Percy Liang, Ludwig Schmidt, Hadi Pouransari, Fartash Faghri
| Challenge: | Existing open-source datasets predominantly apply a single fixed extractor to all webpages. |
| Approach: | They propose to take a Union over different extractors to improve model performance . they show that extractor choice can significantly impact downstream task performance based on content type . |
| Outcome: | The proposed approach can increase the token yield of DCLM-Baseline by 71% while maintaining benchmark performance. |
Spanish HPSG Treebank based on the AnCora Corpus (L18-1)
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| Challenge: | a corpus of HPSG annotated trees for Spanish contains morphosyntactic information, annotations for semantic roles, clitic pronouns and relative clauses. |
| Approach: | They propose to build a Spanish HPSG annotated corpus based on the Spanish corpus AnCora and an HTML format for visualizing the trees in a browser. |
| Outcome: | The proposed corpus contains syntactic and morphological information, semantic roles, clitic pronouns and relative clauses, and has CFG style annotations. |
RealHiTBench: A Comprehensive Realistic Hierarchical Table Benchmark for Evaluating LLM-Based Table Analysis (2025.findings-acl)
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Pengzuo Wu, Yuhang Yang, Guangcheng Zhu, Chao Ye, Hong Gu, Xu Lu, Ruixuan Xiao, Bowen Bao, Yijing He, Liangyu Zha, Wentao Ye, Junbo Zhao, Haobo Wang
| Challenge: | Existing benchmarks for large language models focus on simple, flat table structures. |
| Approach: | They propose a benchmark to evaluate the performance of both Large Language Models and Multimodal LLMs across a variety of input formats for complex tabular data, including LaTeX, HTML, and PNG. |
| Outcome: | The proposed benchmark evaluates the performance of LLMs and Multimodal LLM models across a variety of input formats for complex tabular data, including LaTeX, HTML, and PNG. |
The slurk Interaction Server Framework: Better Data for Better Dialog Models (2022.lrec-1)
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| Challenge: | slurk is a lightweight dialog data collection and testing tool for crowdsourcing platforms. |
| Approach: | They present a lightweight dialog server that allows to set up dialog data collections and run experiments. |
| Outcome: | The slurk software allows to set up dialog data collections and run experiments with no limitations on the number of participants. |
HTML: Hierarchical Topology Multi-task Learning for Semantic Parsing in Knowledge Base Question Answering (2025.findings-acl)
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| Challenge: | Existing approaches struggle with mapping questions to precise logical forms . Existing frameworks struggle with complex mapping of questions to logical form . |
| Approach: | They propose a framework that leverages a hierarchical multi-task learning paradigm to enhance the performance of logical form generation. |
| Outcome: | The proposed framework outperforms supervised fine-tuning methods and training-free ones on large language models. |
Multimodal Table Understanding (2024.acl-long)
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| Challenge: | Existing approaches to understanding tables rely on textual inputs and table images are difficult to access in real-world scenarios. |
| Approach: | They propose a multimodal table understanding problem where the model needs to generate correct responses to various table-related requests based on the given table image. |
| Outcome: | The proposed model outperforms open-source MLLMs on 23 benchmarks under held-in and held-out settings. |
SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents (2024.acl-long)
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| Challenge: | Existing GUI agents interact with the environment through extracted structured data, which can be notably lengthy (e.g., HTML) and occasionally inaccessible (e-book). |
| Approach: | They propose to enhance SeeClick with GUI grounding pre-training and devise a method to automate curation of GUI ground data. |
| Outcome: | The proposed agent improves ScreenSpot, the first realistic GUI grounding benchmark that encompasses mobile, desktop, and web environments. |
WikiDragon: A Java Framework For Diachronic Content And Network Analysis Of MediaWikis (L18-1)
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| Challenge: | WikiDragon is a Java Framework designed to give developers in computational linguistics an intuitive API to build, parse and analyze instances of MediaWikis. |
| Approach: | They introduce WikiDragon, a Java Framework that allows developers to build, parse and analyze instances of MediaWikis on their computers. |
| Outcome: | The framework is based on the Wikipedia, Wiktionary, WikiSource or WikiNews and evaluates link extraction, diachronic network analysis and the impact of different frameworks to text analysis. |
LongTableBench: Benchmarking Long-Context Table Reasoning across Real-World Formats and Domains (2025.findings-emnlp)
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Liyao Li, Jiaming Tian, Hao Chen, Wentao Ye, Chao Ye, Haobo Wang, Ningtao Wang, Xing Fu, Gang Chen, Junbo Zhao
| Challenge: | Evaluating 52 LLMs reveals that only the strongest models maintain robust performance under increasing context lengths and format diversity. |
| Approach: | They propose a benchmark for evaluating long-context reasoning over semi-structured tables across diverse formats, tasks, and domains. |
| Outcome: | The proposed model outperforms compression-based approaches on tasks requiring semantic integration. |
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation (2025.acl-long)
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Yue Yang, Ajay Patel, Matt Deitke, Tanmay Gupta, Luca Weihs, Andrew Head, Mark Yatskar, Chris Callison-Burch, Ranjay Krishna, Aniruddha Kembhavi, Christopher Clark
| Challenge: | Vision-language models struggle to understand text-rich images due to the scarcity of diverse text-only large language data. |
| Approach: | They propose a framework that leverages the coding capabilities of text-only large language models to create synthetic text-rich multimodal data. |
| Outcome: | The proposed framework can generate high-quality instruction-tuning data using Python, HTML, LaTeX and other languages. |
Natural Language Processing Pipeline to Annotate Bulgarian Legislative Documents (2020.lrec-1)
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| Challenge: | The Bulgarian MARCELL corpus consists of 25,283 documents, which are classified into eleven types. |
| Approach: | They present the Bulgarian MARCELL corpus, part of a newly developed multilingual corpus representing the national legislation in seven European countries. |
| Outcome: | The proposed corpus represents the national legislation in seven European countries and the NLP pipeline that turns the web crawled data into structured, linguistically annotated dataset. |
Aria-UI: Visual Grounding for GUI Instructions (2025.findings-acl)
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| Challenge: | Using a multimodal model, GUI agents can ground from language instructions to target elements . relying on HTML or AXTree inputs is a challenge for GUI agents . |
| Approach: | They propose a large multimodal model specifically designed for GUI grounding that adopts a pure vision approach instead of auxiliary inputs. |
| Outcome: | The proposed model outperforms vision-only and AXTree-reliant models on offline and online agents. |
Prompting for Numerical Sequences: A Case Study on Market Comment Generation (2024.lrec-main)
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| Challenge: | Large language models have been applied to data-to-text generation tasks, but their effectiveness is limited to tasks where the input data is structured and their components are represented as words. |
| Approach: | They propose to use large language models to generate text from numerical sequences. |
| Outcome: | The proposed models perform better than natural languages and longer formats, while resembling natural languages yield less effective results. |
WAFFLE: Fine-tuning Multi-Modal Model for Automated Front-End Development (2025.acl-long)
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| Challenge: | Large Language Models (LLMs) have shown promise in generating source code, but two major challenges persist in UI-to-HTML code generation: (1) effectively representing HTML’s hierarchical structure for LLMs; and (2) bridging the gap between the visual nature of UI designs and the text-based format of HTML code. |
| Approach: | They propose a structure-aware attention mechanism that uses a contrastive fine-tuning approach to align LLMs’ understanding of UI images and HTML code. |
| Outcome: | The proposed model outperforms existing methods on the WebSight-Test and Design2Code benchmarks. |
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation (2025.emnlp-main)
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Rabiul Awal, Mahsa Massoud, Aarash Feizi, Zichao Li, Suyuchen Wang, Christopher Pal, Aishwarya Agrawal, David Vazquez, Siva Reddy, Juan A. Rodriguez, Perouz Taslakian, Spandana Gella, Sai Rajeswar
| Challenge: | Existing benchmarks focus on specific aspects of web tasks but lack comprehensive coverage. |
| Approach: | They propose a multilingual benchmark that evaluates three core web tasks: (1) website visual question answering, (2) code editing involving HTML/CSS/JavaScript, and (3) mockup-to-code generation. |
| Outcome: | The proposed model performs well on basic information extraction, but struggles with reasoning and grounding, editing code to preserve functionality, and generating design-to-code that maintains hierarchy and supports multilingual content. |
Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework (2026.acl-long)
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| Challenge: | Recent advances in large language models have demonstrated strong potential for understanding user intent . paper describes system architecture, agent roles, retrieval and scoring methods, knowledge graph schema, and evaluation interfaces . |
| Approach: | They propose a multi-agent research discovery and analysis system that integrates multiple agents to reduce the effort required to find, assess, organize, and understand academic literature. |
| Outcome: | The proposed system reduces the effort required to find, assess, organize, and understand academic literature. |