---
title: "LREC 2026 — all accepted papers, page 5 — the most cited first"
description: "All 944 papers of LREC 2026 · page 5 of 10, the most cited first; those with our summary link to it."
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---
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# LREC 2026: all accepted papers

944 papers · page 5 of 10 · the most cited first · [← LREC 2026](https://md.research.elamur.ai/free/en/venues/lrec/2026/)

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401. **[Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMs](https://md.research.elamur.ai/free/en/papers/moriyama-2026-generation-instruction-preference-dataset-improving/)**Kei Moriyama, Takashi Kodama, Kouta Nakayama*our summary*
402. **[GeoBenchmark: Probing Large Language Models for Geo-Spatial Knowledge ↗](https://aclanthology.org/2026.lrec-1.417/)**Ayomide Abayomi, Jose G. Moreno, Karim Radouane et al.
403. **[GerVLPro: A CEFR-Graded Vocabulary List of L2 Learners' Productive Vocabulary in German](https://md.research.elamur.ai/free/en/papers/michael-2026-gervlpro-cefr-graded-vocabulary-list/)**Noah-Manuel Michael, Anna Huelsing, Andrea Horbach*our summary*
404. **[German Counseling Grounding-Act Corpus (GRACO) ↗](https://aclanthology.org/2026.lrec-1.495/)**Milena Belosevic
405. **[German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies](https://md.research.elamur.ai/free/en/papers/rupprecht-2026-german-general-social-survey-personas/)**Jens Rupprecht, Leon Froehling, Claudia Wagner et al.*our summary*
406. **[GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/)**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*our summary*
407. **[GlossMATE: Multi-Agent Translator Explanations for Glosses](https://md.research.elamur.ai/free/en/papers/yang-2026-glossmate-multi-agent-translator-explanations/)**Changbing Yang, Patrick Littell, Gabriel Bernier-Colborne et al.*our summary*
408. **[Glossed Data in Northern Interior Salish](https://md.research.elamur.ai/free/en/papers/stacey-2026-glossed-data-northern-interior-salish/)**Anna Stacey*our summary*
409. **[Goldfish: Monolingual Language Models for 350 Languages ↗](https://aclanthology.org/2026.lrec-1.300/)**Tyler A. Chang, Catherine Arnett, Zhuowen Tu et al.
410. **[Gradient-Controlled Decoding: A Safety Guardrail for LLMs with Dual-Anchor Steering ↗](https://aclanthology.org/2026.lrec-1.775/)**Purva Chiniya, Kevin Joseph Scaria, Sagar Chaturvedi
411. **[Graph-TempCZ: A Graph Representation of Software Mentions for Predicting Software Usage in Scientific Publications ↗](https://aclanthology.org/2026.lrec-1.619/)**Congfeng Cao, Pengyu Zhang, Jelke Bloem
412. **[Green Bots versus Red Bots: Evaluating Large Language Models for Simulating Persuasion Dynamics in Online Influence Campaigns ↗](https://aclanthology.org/2026.lrec-1.871/)**Majd Eddin Al Ali, Filip Mihai Muntean, Lucia Donatelli et al.
413. **[Gretino: A Greek and Latin Dataset to Benchmark Retrieval Systems in Classical Languages](https://md.research.elamur.ai/free/en/papers/toyin-2026-gretino-greek-latin-dataset-benchmark/)**Hawau Olamide Toyin, Federico Iezzi, Elia Scapini et al.*our summary*
414. **[Grounded Misunderstandings in Asymmetric Dialogue: A Perspectivist Annotation Scheme for MapTask ↗](https://aclanthology.org/2026.lrec-1.392/)**Nan Li, Albert Gatt, Massimo Poesio
415. **[HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning ↗](https://aclanthology.org/2026.lrec-1.407/)**Alexis Correa, Carlos Gómez-Rodríguez, David Vilares
416. **[HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities ↗](https://aclanthology.org/2026.lrec-1.623/)**Shusaku Egami, Aoi Ohta, Tomoki Tsujimura et al.
417. **[HOTATE: A Japanese Dialogue Corpus Annotated with Responses of Private Thoughts and Public Statements](https://md.research.elamur.ai/free/en/papers/toda-2026-hotate-japanese-dialogue-corpus-annotated/)**Yuko Toda, Daisuke Maekawa, Kota Manabe et al.*our summary*
418. **[HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models](https://md.research.elamur.ai/free/en/papers/oepen-2026-hplt-3-0-very-large/)**Stephan Oepen, Nikolay Arefyev, Mikko Aulamo et al.*our summary*
419. **[HalleluBERT: Let Every Token That Has Meaning Bear Its Weight](https://md.research.elamur.ai/free/en/papers/schmitt-2026-hallelubert-let-every-token-that/)**Raphael Schmitt*our summary*
420. **[Harnessing Synergy in Context and Emoji for Joint Detection of Harmful Online Content in Multi-turn Conversations ↗](https://aclanthology.org/2026.lrec-1.791/)**Feiyan Hu, Ciara Anne Byrne, Jiang Zhou et al.
421. **[HateMirage: An Explainable Multi-Dimensional Dataset for Decoding Faux Hate and Subtle Online Abuse ↗](https://aclanthology.org/2026.lrec-1.877/)**Sai Kartheek Reddy Kasu, Shankar Biradar, Sunil Saumya et al.
422. **[HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/)**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*our summary*
423. **[HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings ↗](https://aclanthology.org/2026.lrec-1.30/)**Rasmus T. Aavang, Giovanni Rizzi, Rasmus Tjalk-Bøggild et al.
424. **[High-Order Question Generation in a Multilingual Educational Context](https://md.research.elamur.ai/free/en/papers/ucar-2026-high-order-question-generation-multilingual/)**Suna Seyma Uçar, Itziar Aldabe, Nora Aranberri et al.*our summary*
425. **[Hindsight Quality Prediction Experiments in Multi-Candidate Human-Post-Edited Machine Translation](https://md.research.elamur.ai/free/en/papers/marmonier-2026-hindsight-quality-prediction-experiments-multi/)**Malik Marmonier, Benoît Sagot, Rachel Bawden*our summary*
426. **[HistoriQA-ThirdRepublic: Multi-Hop Question Answering Corpus for Historical Research, Parliamentary Debates from the French Third Republic (1870-1940)](https://md.research.elamur.ai/free/en/papers/pellet-2026-historiqa-thirdrepublic-multi-hop-question/)**Aurelien Pellet, Marie Anna Puren, Julien PEREZ*our summary*
427. **[Historical Medical Knowledge Graphs and Ontologies from the Medical History of British India Corpus (1850-1950) ↗](https://aclanthology.org/2026.lrec-1.618/)**Mehrdad Almasi, Tugce Karatas
428. **[HotelCheckSpan: A Benchmark Dataset for LLM Faithfulness](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-hotelcheckspan-benchmark-dataset-llm-faithfulness/)**Patricia Schmidtova, Ondrej Dusek, Saad Mahamood*our summary*
429. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger et al.*our summary*
430. **[How I Met Your Snowclone: Unsupervised Discovery of Snowclone Patterns in Large Datasets ↗](https://aclanthology.org/2026.lrec-1.622/)**Julien Bezançon, Gaël Lejeune, Marceau Hernandez
431. **[How Long Does a Quick Kiss Take? Studying Event Duration of Light Verb Constructions Using Explicit Word Embeddings ↗](https://aclanthology.org/2026.lrec-1.756/)**Lin de Huybrecht, Geraint A. Wiggins
432. **[How Many Samples Do We Need? A Toolkit for Power-Aware Evaluation Design ↗](https://aclanthology.org/2026.lrec-1.353/)**Angelo Basile, Areg Mikael Sarvazyan, José Ángel González
433. **[How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation ↗](https://aclanthology.org/2026.lrec-1.750/)**Anna Klezovich, Johanna Mesch, Gustav Eje Henter et al.
434. **[How Much Data for Stable Formant Values? Pipeline for Convergence Detection Based on Read Speech](https://md.research.elamur.ai/free/en/papers/sward-2026-how-much-data-stable-formant/)**Kayla Sward, Johan Sjons, Axel G. Ekstrom*our summary*
435. **[How Much Noise Can BERT Handle? Insights from Multilingual Sentence Difficulty Detection ↗](https://aclanthology.org/2026.lrec-1.485/)**Nouran Khallaf, Serge Sharoff
436. **[How Pragmatics Shape Articulation: A Computational Case Study in STEM ASL Discourse ↗](https://aclanthology.org/2026.lrec-1.669/)**Saki Imai, Lee Kezar, Laurel Aichler et al.
437. **[Human Label Variation in Implicit Discourse Relation Recognition ↗](https://aclanthology.org/2026.lrec-1.388/)**Frances Yung, Daniil Ignatev, Merel Scholman et al.
438. **[Human vs LLM in Conversational Repair Annotation: A New Resource and Comparative Study](https://md.research.elamur.ai/free/en/papers/ngo-2026-human-vs-llm-conversational-repair/)**Anh Ngo, Nicolas Rollet, Catherine Pelachaud et al.*our summary*
439. **[Human-Centered Multimodal Fusion for Sexism Detection in Memes with Eye-Tracking, Heart Rate, and EEG Signals ↗](https://aclanthology.org/2026.lrec-1.770/)**Iván Arcos Gabaldón, Paolo Rosso, Elena Gomis Vicent
440. **[Human-in-the-Loop Mass Transcription and Ground Truth Annotation for Challenging Historical Documents ↗](https://aclanthology.org/2026.lrec-1.559/)**Norbert Fischer, Frank Puppe
441. **[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/)**Sabrina Villata, Amon Rapp, Luigi Di Caro et al.*our summary*
442. **[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/)**Luke S. Patterson, Li Wang, Adam Faulkner*our summary*
443. **[I Am Not Them: Persistent Outgroup Bias in Large Language Models Arising from Social Identity Persona Setting ↗](https://aclanthology.org/2026.lrec-1.217/)**Wenchao Dong, Assem Zhunis, Dongyoung Jeong et al.
444. **[I Came, I Saw, I Explained: Benchmarking Multimodal LLMs on Figurative Meaning in Memes](https://md.research.elamur.ai/free/en/papers/zhou-2026-i-came-i-saw-i/)**Shijia Zhou, Saif M. Mohammad, Barbara Plank et al.*our summary*
445. **[IHPP: A Paragraph-Level Dataset for Investigating the Pragmatics of Hyperpartisan Italian News ↗](https://aclanthology.org/2026.lrec-1.157/)**Michele Joshua Maggini, Davide Bassi, Angelo Valente et al.
446. **[IMaSC: A Malayalam Speech Corpus for High-Quality Text-to-Speech Synthesis ↗](https://aclanthology.org/2026.lrec-1.465/)**Deepa P. Gopinath, Thennal D K, Vrinda V. Nair et al.
447. **[IREKIER: An Easy Read Corpus for Basque and Spanish ↗](https://aclanthology.org/2026.lrec-1.128/)**Jesús Calleja, Thierry Etchegoyhen
448. **[Icelandic Math Eval: A Competitive Mathematics Benchmark for Large Language Models ↗](https://aclanthology.org/2026.lrec-1.26/)**Hafsteinn Einarsson, Jökull Ari Haraldsson, Ívar Armin Derayat et al.
449. **[Identifying Contexts of Distress in College Students' Reddit Posts: A Comparative Study of Classical NLP and Large Language Models ↗](https://aclanthology.org/2026.lrec-1.758/)**Carine Graff, Nikhil Krishnaswamy
450. **[Identifying Imaging Follow-Up in Radiology Reports: A Comparative Analysis of Traditional ML and LLM Approaches](https://md.research.elamur.ai/free/en/papers/park-2026-identifying-imaging-follow-up-radiology/)**Namu Park, Giridhar Kaushik Ramachandran, Kevin Lybarger et al.*our summary*
451. **[Implicit Bias in Peer Review: Through the Lens of Language Abstraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-implicit-bias-peer-review-through/)**Xulang Zhang, Rui Mao, Erik Cambria*our summary*
452. **[Improving Latvian Morphosyntactic Parsing with Pretrained Encoders and Analyzer-Constrained Decoding](https://md.research.elamur.ai/free/en/papers/znotins-2026-improving-latvian-morphosyntactic-parsing-pretrained/)**Arturs Znotins*our summary*
453. **[Improving Multilingual Language Models by Aligning Representations through Steering ↗](https://aclanthology.org/2026.lrec-1.164/)**Omar Mohamed Mahmoud, Buddhika Laknath Semage, Thommen George Karimpanal et al.
454. **[Improving Neural Argumentative Stance Classification in Controversial Topics with Emotion-Lexicon Features ↗](https://aclanthology.org/2026.lrec-1.760/)**Mohammad Yeghaneh Abkenar, Weixing Wang, Manfred Stede et al.
455. **[In-Distribution Steering: Balancing Control and Coherence in Language Model Generation](https://md.research.elamur.ai/free/en/papers/vogels-2026-distribution-steering-balancing-control-coherence/)**Arthur Vogels, Benjamin Wong, Yann Choho et al.*our summary*
456. **[Incivility and Rigidity: Evaluating the Risks of Fine-Tuning LLMs for Political Argumentation ↗](https://aclanthology.org/2026.lrec-1.308/)**Svetlana Churina, Kokil Jaidka
457. **[Indirect Question Answering in English, German and Bavarian: A Challenging Task for High- and Low-Resource Languages Alike ↗](https://aclanthology.org/2026.lrec-1.336/)**Miriam Winkler, Verena Blaschke, Barbara Plank
458. **[Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA](https://md.research.elamur.ai/free/en/papers/pei-2026-information-asymmetry-across-language-varieties/)**Renhao Pei, Siyao Peng, Verena Blaschke et al.*our summary*
459. **[Infox-QC: A Quebec-Focused French Corpus for Misinformation Detection and AI Robustness Assessment ↗](https://aclanthology.org/2026.lrec-1.555/)**Moetaz Doghmane, Hazem Amamou, Thiziri Sefsaf et al.
460. **[Injecting Structured Biomedical Knowledge into Language Models:Continual Pretraining vs. GraphRAG ↗](https://aclanthology.org/2026.lrec-1.855/)**Jaafer Klila, Sondes Bannour Souihi, Rahma Boujelbane et al.
461. **[Insights from Romanized Manipuri Social Media Text: A Transliteration Corpus and Variation Analysis](https://md.research.elamur.ai/free/en/papers/salice-2026-insights-romanized-manipuri-social-media/)**Maisang Kamei Salice, Sanasam Ranbir Singh, Priyankoo Sarmah*our summary*
462. **[Insights from Transfer Learning Experiments with Word-in-Context and Word Sense Disambiguation Models](https://md.research.elamur.ai/free/en/papers/mujko-2026-insights-transfer-learning-experiments-word/)**Alp Mujko, Dominik Schlechtweg*our summary*
463. **[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/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*our summary*
464. **[Instruction-Tuned Urdu LLMs: Efficient Adaptation of Llama Models and Evaluation Resources for Urdu ↗](https://aclanthology.org/2026.lrec-1.832/)**Munief Hassan Tahir, Sana Shams, Sarmad Hussain et al.
465. **[Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models ↗](https://aclanthology.org/2026.lrec-1.398/)**Neeraj Gangwar, Suma Bhat, Nickvash Kani
466. **[Integrating Knowledge Graph with Large Language Models for Multi-hop Question Generation ↗](https://aclanthology.org/2026.lrec-1.625/)**Yllias Chali, Al Hasib Mahamud
467. **[Integrating Services, Platforms and Resources into a National Infrastructure Cluster for FAIR Language and Cultural Data](https://md.research.elamur.ai/free/en/papers/pedonese-2026-integrating-services-platforms-resources-into/)**Giulia Pedonese, Daniele Melaccio, Michele Mallia et al.*our summary*
468. **[Integrating TEI, NER/NEL, Textometry, and Linked Data for a Semantically Enriched Interview Corpus](https://md.research.elamur.ai/free/en/papers/stankovic-2026-integrating-tei-ner-nel-textometry/)**Ranka Stankovic, Tamara Vučenović, Biljana Rujević et al.*our summary*
469. **[Intent Recognition in Speech-to-Text Processing in the Context of Natural Interaction with Cognitive Assistive Systems ↗](https://aclanthology.org/2026.lrec-1.793/)**Behnam Ensan, Magnus Jung, Matthias Busch et al.
470. **[Introducing MELI: The Mandarin-English Language Interview Corpus ↗](https://aclanthology.org/2026.lrec-1.468/)**Suyuan Liu, Molly Babel
471. **[Introducing PerMet 1.0: A Metaphor-Annotated Corpus for Persian](https://md.research.elamur.ai/free/en/papers/miri-2026-introducing-permet-1-0-metaphor/)**Mohammad Saeid Miri*our summary*
472. **[Introducing a Bangla Sentence – Gloss Pair Dataset for Bangla Sign Language Translation and Research](https://md.research.elamur.ai/free/en/papers/saha-2026-introducing-bangla-sentence-gloss-pair/)**Neelavro Saha, Rafi Shahriyar, Nafis Ashraf Roudra et al.*our summary*
473. **[Investigating How LLMs Propagate Female Stereotypes: Comparing What Models Say via Prompts with What They Represent in Their Embeddings](https://md.research.elamur.ai/free/en/papers/nunez-2026-investigating-how-llms-propagate-female/)**Andrea Valderrey Nuñez, Jelke Bloem*our summary*
474. **[Investigating Memorization in Language Models Trained via Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/macking-2026-investigating-memorization-language-models-trained/)**Maarten Mäcking, Michaela Regneri*our summary*
475. **[Investigating Proactivity in Multimodal Task-Guidance Dialogues ↗](https://aclanthology.org/2026.lrec-1.5/)**Sofia Brenna, Elisabetta Jezek, Matthias Kraus et al.
476. **[Investigating Reasoning with Hypotheses: The RIP2 Corpus](https://md.research.elamur.ai/free/en/papers/schad-2026-investigating-reasoning-hypotheses-rip2-corpus/)**Ella Schad, Clara Seyfried, Chris Reed*our summary*
477. **[Investigating the Role of Synthetic Data Augmentation and Training Strategies on Improving Low-Resource Language ASR ↗](https://aclanthology.org/2026.lrec-1.442/)**Yun Hao, Reihaneh Amooie, Wietse de Vries et al.
478. **[Irish-BLiMP: A Linguistic Benchmark for Evaluating Human and Language Model Performance in a Low-Resource Setting ↗](https://aclanthology.org/2026.lrec-1.359/)**Josh Mcgiff, Tung Khanh Tran, William Mulcahy et al.
479. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/)**Aidan Mannion, Cécile Macaire, Armand Violle et al.*our summary*
480. **[Is Clinical Text Enough? A Multimodal Study on Mortality Prediction in Heart Failure Patients ↗](https://aclanthology.org/2026.lrec-1.14/)**Oumaima El Khettari, Virgile Barthet, Guillaume Hocquet et al.
481. **[Is One Dataset Enough for Evaluation? Studying Generalizability of Automated Essay Scoring Models ↗](https://aclanthology.org/2026.lrec-1.29/)**Sohaila Eltanbouly, Marwan Sayed, Tamer Elsayed
482. **[Is Semi-Automatic Transcription Useful in Corpus Creation? Preliminary Considerations on the KIParla Corpus](https://md.research.elamur.ai/free/en/papers/simonotti-2026-is-semi-automatic-transcription-useful/)**Martina Simonotti, Ludovica Pannitto, Eleonora Zucchini et al.*our summary*
483. **[Is There Anything More Deceptive than an Obvious Fact? Investigating Implicitness in User-Generated Argumentative Text](https://md.research.elamur.ai/free/en/papers/sviridova-2026-is-there-anything-more-deceptive/)**Ekaterina Sviridova, Elena Cabrio, Serena Villata*our summary*
484. **[Is This Idea Novel? An Automated Benchmark for Judgment of Research Ideas](https://md.research.elamur.ai/free/en/papers/schopf-2026-is-this-idea-novel-automated/)**Tim Schopf, Michael Färber*our summary*
485. **[Issue Detection and Category Classification in Domain-Specific Technical Logbooks ↗](https://aclanthology.org/2026.lrec-1.476/)**Afshin Karimi, Ingmar Hartl, Henrik Tuennermann et al.
486. **[Ithaca Revisited: Benchmarking a Domain-Specific Model for Epigraphy in the Age of LLMs](https://md.research.elamur.ai/free/en/papers/locaputo-2026-ithaca-revisited-benchmarking-domain-specific/)**Alessandro Locaputo, Andrea Brunello, Nicola Saccomanno et al.*our summary*
487. **[J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling](https://md.research.elamur.ai/free/en/papers/nakata-2026-j-chat-japanese-large-scale/)**Wataru Nakata, Kentaro Seki, Hitomi Yanaka et al.*our summary*
488. **[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/)**Seiji Shimizu, Tomohiro Nishiyama, HISADA Shohei et al.*our summary*
489. **[JAPAS: A Benchmark and Neural Approach for Japanese Patent Support Relation Extraction ↗](https://aclanthology.org/2026.lrec-1.330/)**Katsuki Chousa, Ryosuke Sugiura
490. **[JBE-QA: Japanese Bar Exam QA Dataset for Assessing Legal Domain Knowledge ↗](https://aclanthology.org/2026.lrec-1.415/)**Zhihan Cao, Fumihito Nishino, Hiroaki Yamada et al.
491. **[JFC-Recipe: A Dataset for Nutrient Estimation from Japanese User-Generated Cooking Recipes](https://md.research.elamur.ai/free/en/papers/shirai-2026-jfc-recipe-dataset-nutrient-estimation/)**Keisuke Shirai, Yoko Yamakata, Hirotaka Kameko et al.*our summary*
492. **[JMTEB and JMTEB-lite: Japanese Massive Text Embedding Benchmark and Its Lightweight Version ↗](https://aclanthology.org/2026.lrec-1.588/)**Shengzhe Li, Masaya Ohagi, Ryokan Ri et al.
493. **[JPPB: Automatic Construction of a Soft-Labeled Japanese Patient Phrase Bank for Symptom Normalization](https://md.research.elamur.ai/free/en/papers/nishiyama-2026-jppb-automatic-construction-soft-labeled/)**Tomohiro Nishiyama, Mana Kuramoto, Shoko Wakamiya et al.*our summary*
494. **[JSTS-Neg: Japanese Semantic Textual Similarity Dataset for Evaluating Negation Understanding Ability](https://md.research.elamur.ai/free/en/papers/yuasa-2026-jsts-neg-japanese-semantic-textual/)**Reiko Yuasa, Yoshihide Kato, Shigeki Matsubara*our summary*
495. **[JamC-QA: A Multiple-Choice Question Answering Benchmark for Japan-Specific Knowledge ↗](https://aclanthology.org/2026.lrec-1.356/)**Teruaki Oka, Tomohide Shibata, Nao Yoshida
496. **[JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Media](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-jobarabi-arabic-corpus-analysis-job/)**Wajdi Zaghouani, Shimaa Amer Ibrahim, Mabrouka Bessghaier et al.*our summary*
497. **[Joint Identification and Induction of Semantic Frames with Scalable Semi-Supervised Graph Clustering ↗](https://aclanthology.org/2026.lrec-1.786/)**Fabian Barteld, Steffen Remus, Saba Anwar et al.
498. **[Judging Instruction Responses in a Low-Resource Language: A Case Study on Basque](https://md.research.elamur.ai/free/en/papers/ponce-2026-judging-instruction-responses-low-resource/)**David Ponce, Harritxu Gete, Thierry Etchegoyhen et al.*our summary*
499. **[K-MIND: Korean Multimodal INteraction Data for Dyadic Conversation Analysis](https://md.research.elamur.ai/free/en/papers/yang-2026-k-mind-korean-multimodal-interaction/)**Jae Hee Yang, Yuha Shin, Saim Shin et al.*our summary*
500. **[KCIF: Knowledge-Conditioned Instruction Following](https://md.research.elamur.ai/free/en/papers/murthy-2026-kcif-knowledge-conditioned-instruction-following/)**Rudra Murthy, Praveen Venkateswaran, Prince Kumar et al.*our summary*

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