Daiki Chijiwa @dchiji_en

Researcher at NTT / Interests: neural networks, loss landscape, learning theory dchiji.github.io Tokyo Joined June 2021

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Taku Hasegawa @th_freiburg

a month ago

先日、NLPコロキウムでお話しさせていただいた動画がアップロードされました。ご興味がある方はどうぞご覧ください。内容はICML2025 に採択された Portable Reward Tuning のお話です。

NLPコロキウム @nlp_colloquium

a month ago

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NTT広報室 @NTTPR

2 months ago

✨世界初✨ #生成AI のカスタマイズコストを抜本的に低減し、低コスト運用を持続可能にする「ポータブルチューニング」技術を確立しました！本成果は、7/13～19に開催される機械学習分野における最難関国際会議 #ICML2025 にて発表されます #NTTRD

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NTT広報室 @NTTPR

2 months ago

セキュリティに配慮した #LLM の応答精度向上技術を確立しました定型的な自動応答においてLLMの応答からの学習用データの漏洩リスクを抑えつつ応答精度向上に活用が期待されます #NTTRD

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🚀次回の #NLPコロキウムのお知らせ講演者: 長谷川拓さん @th_freiburg @dchiji_en (NTT) 日時: 7/9 (水) 12:00–13:00 JST 世界の変化に応じたモデル更新には高いコストが伴います🌏そこで基盤モデルに柔軟に組み合わせて使えるポータブルな報酬モデルを学習するお話です。nlp-colloquium-jp.github.io/schedule/2025-…

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Shin'ya Yamaguchi @syamaguchi_en

3 months ago

🚀 Happy to share our @CVPR paper, which proposes a post-pre-training method for CLIP to mitigate modality gaps and improve zero-shot performance with just 5 minutes of additional training! We are looking forward to discussing with you at our poster session! #CVPR2025

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Taku Hasegawa @th_freiburg

4 months ago

🎉 Excited to announce our ICML 2025 paper “Portable Reward Tuning: Towards Reusable Fine‑Tuning across Different Pretrained Models,” co‑first‑authored with @dchiji_en 🤝(equal contribution)! #ICML2025 Preprint 👉 arxiv.org/abs/2502.12776

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Shin'ya Yamaguchi @syamaguchi_en

5 months ago

I'm happy to announce that our paper, "Test-time Adaptation for Regression by Subspace Alignment," will be presented at #ICLR2025 on 4/25! We demonstrate that existing TTA methods for classification struggle with regression and propose an effective method using feature alignment.

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Shin'ya Yamaguchi @syamaguchi_en

5 months ago

We have released the preprint and code for our paper, which has been accepted to #CVPR2025! We propose a simple post-pre-training method called CLIP-Refine to mitigate the modality gap in CLIP. Preprint: arxiv.org/abs/2504.12717 Code: github.com/yshinya6/clip-…

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Hidenori Tanaka @Hidenori8Tanaka

5 months ago

AI is reshaping society and ourselves. We're at the wheel, steering this powerful force. But what future do we envision for a human-AI society, and how can we get there safely? We’ve launched "Physics of AI Group" to explore the Philosophy and Physics of Intelligence.

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Machine Learning Journal (@[email protected]) @MLJ_Social

7 months ago

And finally one more open access one: "Transfer learning with pre-trained conditional generative models" by Shin’ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa & Hisashi Kashima (link.springer.com/article/10.100…) #OA

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Hikari Otsuka @oh_thinkingtime

7 months ago

Finally, our paper about Strong Lottery Tickets within Frozen Networks has been accepted & published at #TMLR! I would like to thank the equally contributed authors, Chijiwa-san (@dchiji_en) and López-san, and all the co-authors for their cooperation! openreview.net/forum?id=xpnPY…

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Kazutoshi Shinoda @shino__c

8 months ago

🚀New paper on Theory of Mind accepted @RealAAAI🚀 We present 🍅ToMATO, a benchmark for comprehensively evaluating Theory of Mind in LLMs in a more practical setting. 🔗 Paper: arxiv.org/abs/2501.08838 🔗 Data&Code: github.com/nttmdlab-nlp/T… #AAAI25 #AAAI2025

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Shin'ya Yamaguchi @syamaguchi_en

9 months ago

Also, this work will be presented at the MINT workshop at #NeurIPS2024 tomorrow! Please come to my poster at West Meeting Room 121, 122 (1:00-2:00 PM)😎

Shin'ya Yamaguchi @syamaguchi_en

9 months ago

Also, this work will be presented at the MINT workshop at #NeurIPS2024 tomorrow! Please come to my poster at West Meeting Room 121, 122 (1:00-2:00 PM)😎

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Hikari Otsuka @oh_thinkingtime

9 months ago

Tomorrow, I will present this work about the Strong Lottery Ticket Hypothesis at the compression workshop (West Meeting Room 211-214) of #NeurIPS2024 😁 Let's talk with me about SLTH💪 arxiv.org/abs/2402.14029

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Maya Okawa @MayaOkawa

a year ago

#NeurIPS2023 論文"Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task"のビデオがYouTube で公開されました。ぜひ見てください！ Diffusion Model - Maya Okawa youtu.be/qI3NLutMlx8?si… via @YouTube

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Daiki Chijiwa @dchiji_en

a year ago

now arrived at Vienna because I missed my connecting flight this morning😂

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水槽ゼリー @Jelly_in_a_tank

a year ago

2022年10月に発足したNTT基礎数学研究センタの構成員による特集。どれも面白い。 journal.ntt.co.jp/article/27040

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Shin'ya Yamaguchi @syamaguchi_en

a year ago

I will attend #CVPR2024 next week to present our paper "Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks" at the main conference (Poster Session 5)! In this work, we propose an effective and efficient regularization method for fine-tuning.