--- title: "Who cites TIFA: Accurate and Interpretable — 81 citing papers" description: "81 papers of the Elamur Research library cite «TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question…" canonical: "https://research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [TIFA: Accurate and Interpretable Text-to-Image…](https://md.research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/) / cited by # Who cites «TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering» 81 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering»](https://md.research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/) 1. [**GAIA: a benchmark for General AI Assistants arXiv:2311.12983**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/) 2. **[BLINK: Multimodal Large Language Models Can See but Not Perceive](https://md.research.elamur.ai/free/en/papers/fu-2024-blink-multimodal-large-language-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xingyu Fu, Yushi Hu, Bangzheng Li, et al.*2024 · 206 citations* 3. [**Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations arXiv:2303.18027**Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2023-evaluating-gpt-4-chatgpt-japanese/) 4. **[VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation](https://md.research.elamur.ai/free/en/papers/ku-2024-viescore-explainable-metrics-conditional-image/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Max Ku, Dongfu Jiang, Cong Wei, et al.*2024 · 68 citations* 5. [**The Generative AI Paradox: "What It Can Create, It May Not Understand" arXiv:2311.00059**Peter West, Ximing Lu, Nouha Dziri, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/west-2023-generative-ai-paradox-create-may/) 6. **[Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models' Understanding of Discourse Relations](https://md.research.elamur.ai/free/en/papers/miao-2024-discursive-socratic-questioning-evaluating-faithfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yisong Miao, Hongfu Liu, Wenqiang Lei, et al.*2024 · 16 citations* 7. **[T2I-ReasonBench: Benchmarking Reasoning-Informed Text-to-Image Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-t2i-reasonbench-benchmarking-reasoning-informed/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyue Sun, Rongyao Fang, Chengqi Duan, et al.*2026 · 8 citations* 8. **[T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts](https://md.research.elamur.ai/free/en/papers/huang-2025-t2i-factualbench-benchmarking-factuality-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwei Huang, Wanggui He, Quanyu Long, et al.*2025 · 8 citations* 9. **[IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation](https://md.research.elamur.ai/free/en/papers/tang-2026-igenbench-benchmarking-reliability-text-infographic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinghao Tang, Xueding Liu, Boyuan Zhang, et al.*2026 · 1 citation* 10. **[REVEALER: Reinforcement-Guided Visual Reasoning for Element-Level Text-Image Alignment Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-revealer-reinforcement-guided-visual-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**FuLin Shi, Wenyi Xiao, Leilei Gan, et al.*2026 · 1 citation* 11. **[Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning](https://md.research.elamur.ai/free/en/papers/vaishnav-2026-symbolic-grounding-reveals-representational-bottlenecks/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Mohit Vaishnav, Tanel Tammet*2026 · 1 citation* 12. **[Automatic and Reliable Evaluation for Academic Caption-to-Figure Generation with LMMs](https://md.research.elamur.ai/free/en/papers/ye-2026-automatic-reliable-evaluation-academic-caption/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanghui Ye, Huan Zhao, Qin Zhu, et al.*2026* 13. **[Do NOT Classify and Count: Hybrid Attribute Control Success Evaluation](https://md.research.elamur.ai/free/en/papers/saaro-2026-do-not-classify-count-hybrid/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Felix Matthias Saaro, Pius von Däniken, Mark Cieliebak, et al.*2026* 14. **[FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation](https://md.research.elamur.ai/free/en/papers/shan-2026-factverse-benchmark-factual-consistency-interleaved/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yubo Shan, Kun Zhang, Qiming Xu, et al.*2026* 67 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/) — TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering