mlsanityData to 7 Oct 2026

HyperCLOVA X 8B Omni

arXiv 2601.01792 ↗First posted 5 Jan 2026cs.LG cs.AI cs.CLcited by 3

Not on the map. Why?

Abstract (arXiv)

In this report, we present HyperCLOVA X 8B Omni, the first any-to-any omnimodal model in the HyperCLOVA X family that supports text, audio, and vision as both inputs and outputs. By consolidating multimodal understanding and generation into a single model rather than separate modality-specific pipelines, HyperCLOVA X 8B Omni serves as an 8B-scale omni-pathfinding point toward practical any-to-any omni assistants. At a high level, the model unifies modalities through a shared next-token prediction interface over an interleaved multimodal sequence, while vision and audio encoders inject continuous embeddings for fine-grained understanding and grounding. Empirical evaluations demonstrate competitive performance against comparably sized models across diverse input-output combinations spanning text, audio, and vision, in both Korean and English. We anticipate that the open-weight release of HyperCLOVA X 8B Omni will support a wide range of research and deployment scenarios.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 30 of its 48 references that are in the map. First posted on arXiv 5 Jan 2026.

Builds on

30 of 48 references.

References · 30

  1. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  2. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  3. 2025Qwen2.5-VL Technical Reportcited by 5,418
  4. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  5. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,669
  6. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,790
  7. 2019Towards VQA Models That Can Readcited by 1,696
  8. 2025Gemma 3 Technical Reportcited by 1,686
  9. 2024Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysiscited by 1,375
  10. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,288
  11. 2025SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Featurescited by 1,127
  12. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 960
18 more
  1. 2023GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignmentcited by 946
  2. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 787
  3. 2024Autoregressive Image Generation without Vector Quantizationcited by 644
  4. 2020ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verificationcited by 606
  5. 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 458
  6. 2023Finite Scalar Quantization: VQ-VAE Made Simplecited by 425
  7. 2019Clotho: An Audio Captioning Datasetcited by 354
  8. 2024Better & Faster Large Language Models via Multi-token Predictioncited by 344
  9. 2024Guiding a Diffusion Model with a Bad Version of Itselfcited by 286
  10. 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 245
  11. 2025ImgEdit: A Unified Image Editing Dataset and Benchmarkcited by 225
  12. 2025Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Modelscited by 210
  13. 2024FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMscited by 118
  14. 2025X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Againcited by 105
  15. 2025Ming-Omni: A Unified Multimodal Model for Perception and Generationcited by 62
  16. 2023HAE-RAE Bench: Evaluation of Korean Knowledge in Language Modelscited by 47
  17. 2025Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representationscited by 44
  18. 2025Evaluating Multimodal Generative AI with Korean Educational Standardscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.