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Idan Schwartz @idansc

Assistant Prof. BIU; Chief Scientist https://t.co/ecKXykKnYv; Postdoc TAU; PhD Technion; Interests: Deep Learning, Multi-modal idansc.github.io Tel Aviv, Israel Joined June 2009
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Idan Schwartz retweeted
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Anthropic @AnthropicAI

a month ago

Today we're releasing Claude Opus 4.1, an upgrade to Claude Opus 4 on agentic tasks, real-world coding, and reasoning.

Idan Schwartz retweeted
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OpenAI @OpenAI

a month ago

Our open models are here. Both of them. openai.com/open-models

Idan Schwartz retweeted
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Itai Gat @itai_gat

2 months ago

Excited to share our recent work on corrector sampling in language models! A new sampling method that mitigates error accumulation by iteratively revisiting tokens in a window of previously generated text. With: @shaulneta @urielsinger @lipmanya Link: arxiv.org/abs/2506.06215

Idan Schwartz retweeted
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Computer Science Bar Ilan @ComscienceBiu

3 months ago

Prof. @GalChechik & Dr. @idansc for organized and led the symposium on multimodal deep learning at @BarIlanU’s CS Dept; we explored multimodal deep learning – a fast-growing field pushing the limits of single-modality models.

Idan Schwartz retweeted
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Yftah Ziser @YftahZ

3 months ago

1/6🚀 New #ACL2025Findings: We show you can predict if Chain-of-Thought (CoT) reasoning will succeed — before any tokens are generated! This works with LLMs not specifically trained for reasoning—meaning powerful signals emerge naturally in early processing.

Idan Schwartz retweeted
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Itamar Zimerman @ItamarZimerman

3 months ago

📄🚨New! Attribution methods that assign relevance to tokens are key to extracting explanations from Transformers and LLMs. Yet, all existing approaches produce fragmented and unstructured heatmaps (see image)! Why does this happen? and how can we fix this chronic issue? See🧵1/5

Idan Schwartz retweeted
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Itay Hazan @itayhzn

3 months ago

🧵1/ Text-to-video models generate stunning visuals, but… motion? Not so much. You get extra limbs, objects popping in and out... In our new paper, we present FlowMo -- an inference-time method that reduces temporal artifacts without retraining or architectural changes. 👇

Idan Schwartz retweeted
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AK @_akhaliq

4 months ago

RefVNLI Towards Scalable Evaluation of Subject-driven Text-to-image Generation

Idan Schwartz retweeted
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אוניברסיטת בר-אילן @Bar_ilan

6 months ago

🔬 יום פתוח לתארים מתקדמים בבר-אילן! 📅 יום רביעי 2.4 | 15:00-18:00 | בניין ננוטכנולוגיה פגישות אישיות עם חוקרים מובילים ב-STEM, סיורים במעבדות חדשניות ומידע על מלגות. תואר שני עם תזה או דוקטורט - המפתח שלך לפריצות דרך משפיעות! להרשמה ופרטים >>

Idan Schwartz retweeted
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Yair Shpitzer @yairshp

6 months ago

🔎Unlike methods like DreamBooth (which rely on MSE and fail with a single image), SISO leverages pre-trained similarity metrics (e.g., DINO-based) for better subject fidelity. [1/3]

Idan Schwartz retweeted
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Yair Shpitzer @yairshp

6 months ago

🚀Introducing SISO – a plug-and-play approach for image personalization using just one image!

Idan Schwartz retweeted
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Guy Yariv @guy_yariv

6 months ago

I'm thrilled to announce that Through-The-Mask (TTM) has been accepted to #CVPR2025! TTM is an I2V generation framework that leverages mask-based motion trajectories to enhance object-specific motion and maintain consistency, especially in multi-object scenarios More details👇

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Guy Yariv @guy_yariv

8 months ago

I'm thrilled to announce that Through-The-Mask (TTM) has been accepted to #CVPR2025! TTM is an I2V generation framework that leverages mask-based motion trajectories to enhance object-specific motion and maintain consistency, especially in multi-object scenarios More details👇

Idan Schwartz retweeted
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Hila Chefer @hila_chefer

7 months ago

VideoJAM is our new framework for improved motion generation from @AIatMeta We show that video generators struggle with motion because the training objective favors appearance over dynamics. VideoJAM directly adresses this **without any extra data or scaling** 👇🧵

Idan Schwartz retweeted
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Yftah Ziser @YftahZ

10 months ago

Excited to share our new EMNLP paper! 📄 We uncover that different LLM layers naturally play distinct roles in multitask learning pipelines. 🧠 Layers contribute as both shared and task-specific components—without explicit parameter assignment! - arxiv.org/pdf/2410.20008

Idan Schwartz retweeted
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Jürgen Schmidhuber @SchmidhuberAI

11 months ago

The #NobelPrizeinPhysics2024 for Hopfield & Hinton rewards plagiarism and incorrect attribution in computer science. It's mostly about Amari's "Hopfield network" and the "Boltzmann Machine." 1. The Lenz-Ising recurrent architecture with neuron-like elements was published in…

Idan Schwartz retweeted
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Hila Chefer @hila_chefer

12 months ago

Introducing✨Still-Moving✨—our work from @GoogleDeepMind that lets you apply *any* image customization method to video models🎥 Personalization (DreamBooth)🐶stylization (StyleDrop) 🎨 ControlNet🖼️—ALL in one method! Plus… you can control the amount of generated motion🏃‍♀️ 🧵👇

Idan Schwartz retweeted
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Itai Gat @itai_gat

a year ago

Excited to share Discrete Flow Matching! A discrete flow framework that yields state-of-the-art non-autoregressive modeling. E.g., on code tasks (Pass@1): HumanEval 6.7/11.6, MBPP 6.7/13.1 w/ Tal Remez, @shaulneta, @FelixKreuk, @RickyTQChen, @syhw, @adiyossLC, @lipmanya

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