---
title: "Evaluation & benchmarks — papers, page 8 — Elamur Research"
description: "Evaluation & benchmarks: 684 papers of the Elamur Research library · page 8 of 8 · 626–684, the most cited first."
canonical: "https://research.elamur.ai/free/en/topics/evaluation-benchmarks/page/8/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/evaluation-benchmarks/page/8/)

[home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) / page 8

# 📏 Evaluation & benchmarks

684 papers · page 8 of 8 · 626–684 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

How systems are measured: benchmarks, metrics, human judgements and what the numbers mean.

## Papers (684)

[← prev](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/page/7/) [1](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) … [7](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/page/7/) **8**

626. **[HotelCheckSpan: A Benchmark Dataset for LLM Faithfulness](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-hotelcheckspan-benchmark-dataset-llm-faithfulness/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Patricia Schmidtova, Ondrej Dusek, Saad Mahamood*2026*
627. **[HumaniCA: A Benchmark Resource for the Detection of Users' Ascription of Humanness to Conversational Agents](https://md.research.elamur.ai/free/en/papers/villata-2026-humanica-benchmark-resource-detection-users/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sabrina Villata, Amon Rapp, Luigi Di Caro, et al.*2026*
628. **[HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection](https://md.research.elamur.ai/free/en/papers/patterson-2026-hybridcodeauthorship-benchmark-dataset-line-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Luke S. Patterson, Li Wang, Adam Faulkner*2026*
629. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*
630. **[J-ClinicalBench: A Benchmark for Evaluating Large Language Models on Practical Clinical Tasks in Japanese](https://md.research.elamur.ai/free/en/papers/shimizu-2026-j-clinicalbench-benchmark-evaluating-large/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Seiji Shimizu, Tomohiro Nishiyama, HISADA Shohei, et al.*2026*
631. **[KinyCOMET: Automatic Evaluation of Machine Translation Systems for Kinyarwanda–English](https://md.research.elamur.ai/free/en/papers/mazimpaka-2026-kinycomet-automatic-evaluation-machine-translation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Prince Chris Mazimpaka, Jan Nehring, Samuel Rutunda, et al.*2026*
632. **[Logic-Level Evaluation of Logical Table-to-Text Generation](https://md.research.elamur.ai/free/en/papers/trigg-2026-logic-level-evaluation-logical-table/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lena Trigg, Dean F. Hougen, Ahsan Bilal*2026*
633. **[Lost in Translation: Repurposing semantic similarity benchmarks for evaluating lexical-semantic consistency in LLM-based machine translation](https://md.research.elamur.ai/free/en/papers/ye-2026-lost-translation-repurposing-semantic-similarity/) [Workshop on Resources and Representations for Under-Resourced Languages and Domains](https://md.research.elamur.ai/free/en/venues/resourceful/)**Quin Ye, Jelke Bloem*2026*
634. **[Machine translation Evaluation Eng-Thai MQM Ranking dataset](https://md.research.elamur.ai/free/en/papers/phuangrot-2026-machine-translation-evaluation-eng-thai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Phichet Phuangrot, Natdanai Trintawat, Kanawat Vilasri, et al.*2026*
635. [**Meaning Over Morphology: A Multi-Metric Benchmark of LLMs for Bangla Dialect Translation Proceedings of the First Workshop on Dialects in NLP –- A Resource Perspective**Soumik Deb Niloy, Subhey Sadi Rahman, Mahbub E Sobhani, et al.*2026*](https://md.research.elamur.ai/free/en/papers/niloy-2026-meaning-over-morphology-multi-metric/)
636. **[Meaning-Making Process and Error Dynamics in ChatGPT-Mediated Translation](https://md.research.elamur.ai/free/en/papers/mihalache-2026-meaning-making-process-error-dynamics/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Iulia Mihalache, María-José Varela Salinas*2026*
637. **[Metric Grammars: A usage-based grammatical formalism that supports generation, parsing and morphological innovation](https://md.research.elamur.ai/free/en/papers/tabor-2026-metric-grammars-usage-based-grammatical/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Whitney Tabor, Hyosun Lee*2026*
638. **[MEUR: A Benchmark for Evaluating Vision-Language Models on Multimodal Event Understanding and Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-meur-benchmark-evaluating-vision-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zimu Wang, Yuqi Wang, Tong Chen, et al.*2026*
639. **[MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation](https://md.research.elamur.ai/free/en/papers/riley-2026-mqm-re-annotation-technique-collaborative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Riley, Daniel Deutsch, Mara Finkelstein, et al.*2026*
640. **[mSCoRe: A Multilingual and Scalable Benchmark for Skill-based Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/ngo-2026-mscore-multilingual-scalable-benchmark-skill/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen*2026*
641. **[MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/pan-2026-mt-video-bench-holistic-video/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaning Pan, Qianqian Xie, Guohui Zhang, et al.*2026*
642. **[Multi-dimensional Evaluation of Character-Authentic Dialogue Models Learned from Question-Answer Data](https://md.research.elamur.ai/free/en/papers/otsuka-2026-multi-dimensional-evaluation-character-authentic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Atsushi Otsuka, Kazuya Matsuo, Kenta Hama, et al.*2026*
643. **[NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/westhelle-2026-negnli-br-brazilian-portuguese-benchmark/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Matheus Westhelle, Viviane Moreira*2026*
644. **[On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-temperature-constrained-non-deterministic-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weichuan Wang, Mingyang Liu, Chen Ma, et al.*2026*
645. **[OpenSubtitles2024: A Massively Parallel Dataset of Movie Subtitles for MT Development and Evaluation](https://md.research.elamur.ai/free/en/papers/tiedemann-2026-opensubtitles2024-massively-parallel-dataset-movie/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Joerg Tiedemann, Hengyu Luo*2026*
646. [**Parsing Arabic Dialects Revisited: New Benchmarks, Models, and Insights**Ahmed Farouk Zakaria Elshabrawy, Go Inoue, Muhammed AbuOdeh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/elshabrawy-2026-parsing-arabic-dialects-revisited-new/)
647. **[Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-Making](https://md.research.elamur.ai/free/en/papers/yoshikawa-2026-persona-aware-evaluation-cognitive-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki*2026*
648. **[Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/asgari-2026-quantifying-metric-model-agreement-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arash Asgari, Huan Wu, Amirreza Naziri, et al.*2026*
649. **[Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation](https://md.research.elamur.ai/free/en/papers/thellmann-2026-quantifying-impact-translation-errors-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber, et al.*2026*
650. **[Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses](https://md.research.elamur.ai/free/en/papers/nguyen-2026-questionnaire-meets-llm-benchmark-empirical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, et al.*2026*
651. [**QuranicMMLU: A Cognitively-Aware Benchmark for Evaluating Generative AI Solutions on Quranic Linguistic Knowledge arXiv:2609.22038 · Arabic NLP 2026**Rawan El Ghali; Umm Kulsoom; Anas Madkoor; Dima Faris Alsaudi; Roaa Abdelmagid; Roaa Ibrahim; Raghad Mousa; Hamza Aljaji; Abdullah Khanafer; Abdallah Alkanani; Salah Feras Alali; Rawan Khaled Mohamed;, Ehsaneddin Asgari*2026*](https://md.research.elamur.ai/free/en/papers/ghali-2026-quranicmmlu-cognitively-aware-benchmark-evaluating/)
652. **[Reference-free Evaluation at Inference for NER/NEL over OCRed Historical Texts](https://md.research.elamur.ai/free/en/papers/nguyen-2026-reference-free-evaluation-inference-ner/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tien-Nam Nguyen, Adam Jatowt, Ahmed Hamdi, et al.*2026*
653. **[Rethinking Evaluation in Retrieval-Augmented Personalized Dialogue: A Cognitive and Linguistic Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2026-rethinking-evaluation-retrieval-augmented-personalized/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tianyi Zhang, David Traum*2026*
654. **[Rethinking Gender Annotation for Bias Evaluation in Machine Translation: Can LLMs Improve Reliability?](https://md.research.elamur.ai/free/en/papers/manna-2026-rethinking-gender-annotation-bias-evaluation/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Chiara Manna, Argentina Anna Rescigno, Eva Vanmassenhove*2026*
655. **[Rethinking Role-Playing Evaluation: Anonymous Benchmarking and A Systematic Study of Personality Effects](https://md.research.elamur.ai/free/en/papers/peng-2026-rethinking-role-playing-evaluation-anonymous/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Ji-Lun Peng, Yun-Nung Chen*2026*
656. **[SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series](https://md.research.elamur.ai/free/en/papers/pennec-2026-sagaqa-multi-hop-reasoning-benchmark/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Galann Pennec, Zhengyuan Liu, Nicholas Asher, et al.*2026*
657. **[Scoring the Translation: On Target Automatic Keyword-Based Evaluation of Machine Translation in the Sports Domain](https://md.research.elamur.ai/free/en/papers/steingrimsson-2026-scoring-translation-target-automatic-keyword/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Steinþór Steingrímsson, Einar Freyr Sigurðsson*2026*
658. **[Semantic Parsing for Evaluating Large Language Models: Separating Linguistic Abilities with YARN](https://md.research.elamur.ai/free/en/papers/vergnette-2026-semantic-parsing-evaluating-large-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rémi DE VERGNETTE, Maxime Amblard*2026*
659. **[STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*
660. **[The Potential for Misleading Results in Text Sanitisation with Standard Evaluation Metrics](https://md.research.elamur.ai/free/en/papers/zhang-2026-potential-misleading-results-text-sanitisation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dan Zhang, Mark Anderson*2026*
661. **[To Overfit or Not to Overfit? An Evaluation of HTR Workflow on 17Th-18Th Century French Corpus](https://md.research.elamur.ai/free/en/papers/tiger-2026-overfit-or-not-overfit-evaluation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marine Tiger*2026*
662. **[TryggLLM: A Benchmark for Evaluating LLM Safety in Norwegian](https://md.research.elamur.ai/free/en/papers/touileb-2026-tryggllm-benchmark-evaluating-llm-safety/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Samia Touileb, Truls Pedersen, Isabell Stinessen Haugen*2026*
663. **[ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vimedcss-vietnamese-medical-code-switching/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tung X. Nguyen, Nhu Vo, Giang-Son Nguyen, et al.*2026*
664. **[Which Way Does Time Flow? A Psychophysics-Grounded Evaluation for Vision–Language Models](https://md.research.elamur.ai/free/en/papers/matta-2026-which-way-does-time-flow/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Shiho Matta, Lis Kanashiro Pereira, Peitao Han, et al.*2026*
665. **[Who Generates More Empathetic Responses–-Humans or LLMs? A Comparative Evaluation with Human and LLM Judges](https://md.research.elamur.ai/free/en/papers/welivita-2026-who-generates-more-empathetic-responses/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Anuradha Welivita, Fawzia Zeitoun, Pearl Pu*2026*
666. [**YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models**Mahmoud Reda, Salam Khalifa, Reham Marzouk, et al.*2026*](https://md.research.elamur.ai/free/en/papers/reda-2026-yallamorph-benchmark-evaluating-arabic-morphological/)
667. [**ALHD: A Large-Scale and Multigenre Benchmark Dataset for Arabic LLM-Generated Text Detection arXiv:2510.03502**Ali Khairallah, Arkaitz Zubiaga*2025*](https://md.research.elamur.ai/free/en/papers/khairallah-2025-alhd-large-scale-multigenre-benchmark/)
668. [**ArFake: A Robust Framework for Multi-Dialect Arabic Speech Spoofing Detection Benchmark arXiv:2509.22808**Mohamed Elsetohy, Alhassan Ehab, Ali Mekky, et al.*2025*](https://md.research.elamur.ai/free/en/papers/elsetohy-2025-arfake-robust-framework-multi-dialect/)
669. [**Assessing the Agreement Competence of Large Language Models**Alba Táboas García, Leo Wanner*2025*](https://md.research.elamur.ai/free/en/papers/garcia-2025-assessing-agreement-competence-large-language/)
670. [**Evaluating the Performance of Transformers in Translating Low-Resource Languages through Akkadian Proceedings of the First Workshop on Comparative Performance Evaluation: From Rules to Language Models**Daniel A. Jones, Ruslan Mitkov*2025*](https://md.research.elamur.ai/free/en/papers/jones-2025-evaluating-performance-transformers-translating-low/)
671. **[Evaluation on Chinese Multiturn Instruction Following Capability of Large Language Models (大语言模型的中文多轮指令遵循能力评测研究)](https://md.research.elamur.ai/free/en/papers/zhu-2025-evaluation-chinese-multiturn/) [Journal of Chinese Information Processing](https://md.research.elamur.ai/free/en/venues/journal-of-chinese-information-processing/)**Qin Zhu (朱秦), Junliang He (何俊亮), Xipeng Qiu (邱锡鹏), et al.*2025*
672. **[Proceedings of the 1st Workshop on Benchmarks, Harmonization, Annotation, and Standardization for Human-Centric AI in Indian Languages (BHASHA 2025)](https://md.research.elamur.ai/free/en/papers/bhattacharya-2025-proceedings-1st-workshop-benchmarks-harmonization/) [Workshop on Benchmarks, Harmonization, Annotation, and Standardization for Human-Centric AI in Indian Languages](https://md.research.elamur.ai/free/en/venues/bhasha/)**Arnab Bhattacharya, Pawan Goyal, Saptarshi Ghosh, et al.*2025*
673. **[Robustness Evaluation of ChatGPT Against Chinese Adversarial Attacks (中文对抗攻击下的ChatGPT鲁棒性评估)](https://md.research.elamur.ai/free/en/papers/zhang-2025-robustness-evaluation-chatgpt/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yunting Zhang (张云婷), Lin Ye (叶麟), Baisong Li (李柏松), et al.*2025*
674. [**Towards stable AI systems for Evaluating Arabic Pronunciations arXiv:2508.19587 · 4th International Conference on NLP and Machine Learning Trends 2025**Hadi Zaatiti, Hatem Hajri, Osama Abdullah, et al.*2025*](https://md.research.elamur.ai/free/en/papers/zaatiti-2025-towards-stable-ai-systems-evaluating/)
675. **[Building and evaluating a Japanese-English bilingual model by vocabulary-replacing continual pretraining (語彙置換継続事前学習による日英バイリンガルモデルの構築と評価)](https://md.research.elamur.ai/free/en/papers/asaba-2024-building-evaluating-japanese-english/) [Annual Meeting of the Association for Natural Language Processing](https://md.research.elamur.ai/free/en/venues/annual-meeting-of-the-association-for-natural-language-processing/)**麻場直喜, 野崎雄太, 中島大, et al.*2024*
676. **[Evaluating Large Language Models: A Survey of Research Progress (大语言模型评测综述)](https://md.research.elamur.ai/free/en/papers/luo-2024-evaluating-large-language/) [Journal of Chinese Information Processing](https://md.research.elamur.ai/free/en/venues/journal-of-chinese-information-processing/)**Wen Luo (罗文), Houfeng Wang (王厚峰)*2024*
677. [**Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care arXiv:2406.15966**Hassan Alhuzali, Ashwag Alasmari*2024*](https://md.research.elamur.ai/free/en/papers/alhuzali-2024-evaluating-effectiveness-foundational-models-q/)
678. [**Generation and Evaluation of English Grammar Multiple-Choice Cloze Exercises**Nicolò Donati, Matteo Periani, Paolo Di Natale, et al.*2024*](https://md.research.elamur.ai/free/en/papers/donati-2024-generation-evaluation-english-grammar-multiple/)
679. **[Construction of Chinese Sentence-Level Gender-Unbiased Data Set and Evaluation of Gender Bias in Pre-Training Language Model (中文句子级性别无偏数据集构建及预训练语言模型的性别偏度评估)](https://md.research.elamur.ai/free/en/papers/zhao-2023-construction-chinese-sentence/) [Journal of Chinese Information Processing](https://md.research.elamur.ai/free/en/venues/journal-of-chinese-information-processing/)**Jishun Zhao (赵继舜), Bingjie Du (杜冰洁), Pengyuan Liu (刘鹏远), et al.*2023*
680. [**The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment**Ben Hagag, Reut Tsarfaty*2023*](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/)
681. **[Qu'apporte BERT à l'analyse syntaxique en constituants discontinus ? Une suite de tests pour évaluer les prédictions de structures syntaxiques discontinues en anglais (What does BERT contribute to discontinuous constituency parsing ? A test suite to evaluate discontinuous constituency structure predictions in English)](https://md.research.elamur.ai/free/en/papers/coavoux-2020-qu-apporte-bert-l-analyse/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Maximin Coavoux*2020*
682. [**Evaluating Lemmatization Models for Machine-Assisted Corpus-Dictionary Linkage**Kevin Black, Eric Ringger, Paul Felt, et al.*2014*](https://md.research.elamur.ai/free/en/papers/black-2014-evaluating-lemmatization-models-machine-assisted/)
683. **[Towards a Semantic Annotation of English Television News - Building and Evaluating a Constraint Grammar FrameNet](https://md.research.elamur.ai/free/en/papers/yang-2012-semantic-annotation-english-television-news/) [Pacific Asia Conference on Language, Information and Computation (PACLIC)](https://md.research.elamur.ai/free/en/venues/paclic/)**Shaohua Yang, Hai Zhao, Bao-liang Lu*2012*
684. **[Collection and Evaluation of Broadcast News Data for Arabic](https://md.research.elamur.ai/free/en/papers/afify-2004-collection-evaluation-broadcast-news-data/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mohamed Afify, Ossama Emam*2004*

[← prev](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/page/7/) [1](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) … [7](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/page/7/) **8**