---
title: "SemEval-2026 Task 8 — paper by Rosenthal et al. (2026)"
description: "This shared task evaluates retrieval-augmented generation in multi-turn dialogue. 39 references, cited by 26 papers here."
authors: ["Sara Rosenthal", "Vraj Shah", "Yannis Katsis", "Marina Danilevsky"]
year: 2026
venue: "Proceedings of the 20th International Workshop on Semantic Evaluation (2026)"
source: "https://aclanthology.org/2026.semeval-1.447/"
doi: "10.18653/v1/2026.semeval-1.447"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/rosenthal-2026-semeval-2026-task-8-mtrageval/"
---
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# SemEval-2026 Task 8: MTRAGEval: Evaluating Multi-Turn RAG Conversations

**Authors:** [Sara Rosenthal](https://md.research.elamur.ai/free/en/authors/sara-rosenthal/), [Vraj Shah](https://md.research.elamur.ai/free/en/authors/vraj-shah/), [Yannis Katsis](https://md.research.elamur.ai/free/en/authors/yannis-katsis/) and [Marina Danilevsky](https://md.research.elamur.ai/free/en/authors/marina-danilevsky/) · **Year:** 2026 · **Venue:** [Proceedings of the 20th International Workshop on Semantic Evaluation (2026)](https://md.research.elamur.ai/free/en/venues/semeval/) ([SemEval 2026](https://md.research.elamur.ai/free/en/venues/semeval/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.semeval-1.447/) · [PDF](https://aclanthology.org/2026.semeval-1.447.pdf) · [DOI 10.18653/v1/2026.semeval-1.447](https://doi.org/10.18653/v1/2026.semeval-1.447) · [OpenAlex](https://openalex.org/W7166872946)

**Citations:** 0 citations (OpenAlex, 2026-10-14) · [26](https://md.research.elamur.ai/free/en/papers/rosenthal-2026-semeval-2026-task-8-mtrageval/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
This shared task evaluates retrieval-augmented generation in multi-turn dialogue. In that setting, follow-up questions often depend on earlier turns, cannot be answered from the corpus, or are ambiguous. The organizers split the pipeline into three subtasks: retrieval only (A), answer generation from gold passages (B), and full end-to-end RAG (C). Participants trained and validated on the existing MTRAG benchmark. Systems were then tested on a hidden set drawn from the new MTRAG-UN benchmark. That benchmark consists of human-written conversations and emphasizes unanswerable, underspecified, non-standalone and clarification-seeking turns.

Strong retrieval systems typically rewrote context-dependent queries into self-contained ones and then applied reranking and rank fusion. The best generation systems mostly combined several LLMs without task-specific training. When systems had to retrieve passages themselves rather than receive gold ones, the top score fell sharply, which shows how retrieval mistakes propagate into answers. Almost no system handled ambiguous questions well, and unanswerable questions also remained hard. The test data is openly released under Apache 2.0, giving the community a reusable benchmark for conversational RAG.

## Key points
- Participation: 107 registered teams and 92 submissions from 48 teams. Subtask A had 38 teams, B had 26 and C had 29.
- Test set: 507 of the 666 MTRAG-UN tasks, restricted to the CLAPNQ, FiQA, Govt and Cloud domains. These comprise 285 answerable, 47 partially answerable, 97 unanswerable and 78 underspecified tasks; the underspecified ones were a surprise challenge excluded from the leaderboard. The training data was MTRAG, with 110 conversations and 842 tasks. Mixtral 8x7B was not allowed because it had been used as the generator during dataset creation.
- Subtask A winner: AILS-NTUA. Its pipeline generated five query rewrites, retrieved with Elser-v1, reranked with cohere-rerank-v4.0-pro and merged the lists with weighted RRF.
- Subtask B winner: RaguTeam, using an ensemble of 7 LLMs with GPT-4o-mini selecting the best answer. Subtask C winner: GenAIus, which combined hybrid retrieval with zero-shot prompting.
- Gap between B and C: the best H-Mean dropped by about 20 points from B to C.
- Underspecified questions: half of the Subtask B teams, including the top-ranked ones, scored zero on them.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Sara Rosenthal, Vraj Shah, Yannis Katsis and Marina Danilevsky. 2026. SemEval-2026 Task 8: MTRAGEval: Evaluating Multi-Turn RAG Conversations. Proceedings of the 20th International Workshop on Semantic Evaluation (2026).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{rosenthal2026semeval,
  title = {{SemEval-2026 Task 8: MTRAGEval: Evaluating Multi-Turn RAG Conversations}},
  author = {Sara Rosenthal, Vraj Shah, Yannis Katsis and Marina Danilevsky},
  booktitle = {Proceedings of the 20th International Workshop on Semantic Evaluation (2026)},
  year = {2026},
  doi = {10.18653/v1/2026.semeval-1.447},
  url = {https://doi.org/10.18653/v1/2026.semeval-1.447}
}
```

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## References

39 references, 17 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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33. Murat Çelik, Nejla Dinçer, Can Ersoy, Mert Toprak, Barış Tan Ünal, Riccardo Coppola, and Flavio Giobergia. 2026. Polito Team at semeval-2026 task 8: Scaling multi-turn RAG: High-performance parallelized pipeline for the MTRAG benchmark. In Proceedings of the 20th International Workshop on Semantic… [find](https://scholar.google.com/scholar?q=Murat+%C3%87elik%2C+Nejla+Din%C3%A7er%2C+Can+Ersoy%2C+Mert+Toprak%2C+Bar%C4%B1s%CC%A7+Tan+%C3%9Cnal%2C+Riccardo+Coppola%2C+and+Flavio+Giobergia%2E+2026%2E+Polito+Team+at+semeval%2D2026+task+8%3A+Scaling+multi%2Dturn+RAG%3A+High%2Dperformance+paralleli)
34. Jerin Romijah Tuli, MD. Sartaj Alam Pritom, and Talukder Naemul Hasan Naem. 2026. Mind_Flayer at semeval-2026 task 8:dualrag:answerability-aware generation for multi-turn RAG conversations. In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego, California… [find](https://scholar.google.com/scholar?q=Jerin+Romijah+Tuli%2C+MD%2E+Sartaj+Alam+Pritom%2C+and+Talukder+Naemul+Hasan+Naem%2E+2026%2E+Mind%5FFlayer+at+semeval%2D2026+task+8%3Adualrag%3Aanswerability%2Daware+generation+for+multi%2Dturn+RAG+conversations%2E+In+Proceed)
35. Finn Wigger, Maximilian Podolsky, Merle Wilmink, Zelong Peng, Shaghayegh Kolli, and Jana Diesner. 2026. [RAGTUM at semeval-2026 task 8: Contextual query rewriting and dense retrieval for multi-turn RAG](https://md.research.elamur.ai/free/en/papers/wigger-2026-ragtum-semeval-2026-task-8/). In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego…
36. Jin Rui Yang, Yichong Chen, and Liang Yang. 2026. [DUTIR at semeval-2026 task 8: A hybrid retrieval and faithfulness-guarded framework for multi-turn RAG](https://md.research.elamur.ai/free/en/papers/yang-2026-dutir-semeval-2026-task-8/). In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego, California, United States. Association for Com…
37. Suveyda Yeniterzi and Reyyan Yeniterzi. 2026. [GenAIus at semeval-2026 task 8: Beyond retrieval with relevance-aware RAG for faithful multi-turn generation](https://md.research.elamur.ai/free/en/papers/yeniterzi-2026-genaius-semeval-2026-task-8/). In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego, California, United States. Association for C…
38. Jiaqi Zhang, Wenbin Duan, Yingqi Zhang, Yan Li, and Binyang Li. 2026. uir_cis at semeval-2026 task 8: A unified lightweight pipeline for multi-turn RAG evaluation. In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego, California, United States. Associati… [find](https://scholar.google.com/scholar?q=Jiaqi+Zhang%2C+Wenbin+Duan%2C+Yingqi+Zhang%2C+Yan+Li%2C+and+Binyang+Li%2E+2026%2E+uir%5Fcis+at+semeval%2D2026+task+8%3A+A+unified+lightweight+pipeline+for+multi%2Dturn+RAG+evaluation%2E+In+Proceedings+of+the+20th+Internati)
39. Ke Zhou and Yi-Shan Lin. 2026. [UTRAG at semeval-2026 task 8: History-aware query rewriting and lora-finetuned generation for multi-turn rag](https://md.research.elamur.ai/free/en/papers/zhou-2026-utrag-semeval-2026-task-8/). In Proceedings of the 20th International Workshop on Semantic Evaluation (SemEval-2026), San Diego, California, United States. Association for Computational Li…

*Updated 31 October 2026*