| Feb 14, 2026 | We released Seed 2.0. Building on our efforts to improve generalizable reasoning in Seed 1.8, I was responsible for extending these capabilities across domains and modalities. |
| Jan 26, 2026 | We propose the COD framework that accurately predicts LLM downstream performance before training, achieving a 1.36% average prediction error on a 70B parameter model. This work has been accepted in ICLR 2026. Read more |
| Dec 18, 2025 | We released Seed 1.8. I was responsible for improving the model’s generalizable reasoning capabilities. |
| Aug 21, 2025 | We released Seed-OSS model. I was responsible for enhancing the model’s reasoning density, aenabling it to maintain longer chains of thought and tackle more challenging problems. |
| Jun 25, 2025 | We released Seed 1.6. I was responsible for the multimodal mixed continual training (MMCT) stage, enabling the model to achieve strong native multimodal capabilities without sacrificing its text performance. |
| Aug 30, 2024 | We propose the Faster-GCG algothrim, a foundamental and efficient discrete optimization approach for jailbreak attacks against large language models. Read more |
| Aug 1, 2024 | We propose the ADBM model, which can significantly improves the robustness of visual models on OOD examples. We show theoretically and empirically that ADBM outperforms the original DDPM. This work has been accepted in ICLR 2025. Read more |
| Jul 7, 2024 | We released the PartImageNet++ dataset and further improved the part-based recogntion models. The paper has been accepted by ECCV 2024. Read more |
| Mar 18, 2024 | One paper on the relation between adversarial robustness and privacy is accepted by IEEE TIFS 2024. Read more |
| Feb 26, 2024 | One paper on achiving zero-shot adversarial robustness with multimodal CLIP models is accepted by CVPR 2024. The proposed LAAT method uses language-driven anchors to guide adversarial training of vision models. Read more |
| May 27, 2023 | One paper on how to improving robustness of object detectors with upstream adversarial pre-training is available on arXiv. Read more |
| Jan 18, 2023 | One paper inspired by cognitive psychology theory is accepted by IEEE TPAMI 2023. The proposed ROCK method can significantly improve both adversarial robusntess and generalization on out-of-distribution examples. Read more |
| Jul 14, 2022 | One paper is accepted by IJCV 2022, which is an extended version of the BPR paper. Read more |
| Mar 1, 2021 | One paper on instance segmentatiion is accepted to CVPR 2021. The proposed BPR method reached 1st place on the Cityscapes leaderboard (instance segmentation track). Read more |