Surajit Dasgupta @zephyrzilla
Machine Learning @servicenow | Previously ML, NLP @FactSet | Opinions are my own. Hyderabad, India Joined January 2012-
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Surajit Dasgupta retweeted
🚀 Introducing Qwen3-Omni — the first natively end-to-end omni-modal AI unifying text, image, audio & video in one model — no modality trade-offs! 🏆 SOTA on 22/36 audio & AV benchmarks 🌍 119L text / 19L speech in / 10L speech out ⚡ 211ms latency | 🎧 30-min audio…
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Surajit Dasgupta retweeted
Today Thinking Machines Lab is launching our research blog, Connectionism. Our first blog post is “Defeating Nondeterminism in LLM Inference” We believe that science is better when shared. Connectionism will cover topics as varied as our research is: from kernel numerics to…
Surajit Dasgupta retweeted
“Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search” has been accepted as a spotlight at #NeurIPS2025 ✨ Paper: arxiv.org/abs/2503.04412 Blog: sakana.ai/ab-mcts/ GitHub: github.com/SakanaAI/TreeQ…
“Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search” has been accepted as a spotlight at #NeurIPS2025 ✨ Paper: arxiv.org/abs/2503.04412 Blog: sakana.ai/ab-mcts/ GitHub: github.com/SakanaAI/TreeQ…
Surajit Dasgupta retweeted
🚀 LongCat-Flash-Thinking: Smarter reasoning, leaner costs! 🏆 Performance: SOTA open-source models on Logic/Math/Coding/Agent tasks 📊 Efficiency: 64.5% fewer tokens to hit top-tier accuracy on AIME25 with native tool use, agent-friendly ⚙️ Infrastructure: Async RL achieves a…
Surajit Dasgupta retweeted
Most RL for LLMs involves only 1 step of RL. It’s a contextual bandit problem and there’s no covariate shift because the state (question, instruction) is given. This has many implications, eg DAgger becomes SFT, and it is trivial to design Expectation Maximisation (EM) maximum…
Surajit Dasgupta retweeted
reminded of this paragraph from gsm8k paper, 2021 :)
reminded of this paragraph from gsm8k paper, 2021 :) https://t.co/lmubBMBFIb
Surajit Dasgupta retweeted
🚨 SLAM Labs presents Apriel-5B! And it lands right in the green zone 🚨 Speed ⚡ + Accuracy 📈 + Efficiency 💸 This model punches above its weight, beating bigger LLMs while training on a fraction of the compute. Built with Fast-LLM, our in-house training stack. 🧵👇
Surajit Dasgupta retweeted
Retweet if you want llama.cpp added here 👇
Retweet if you want llama.cpp added here 👇
I just sponsored python. Go sponsor your open source dependencies! github.com/sponsors/pytho…
I just sponsored psf. Go sponsor your open source dependencies! github.com/sponsors/psf?o…
Surajit Dasgupta retweeted
Happy to announce AlignVLM📏: a novel approach to bridging vision and language latent spaces for multimodal understanding in VLMs! 🌍📄🖼️ 🔗 Read the paper: arxiv.org/abs/2502.01341 🧵👇 Thread
Surajit Dasgupta retweeted
Apparently if you don't subscribe to the orthodoxy of a bunch of SF AI bros who got into deep learning after 2020 and who think of it as a cult identity rather than an engineering field, you must be anti deep learning
Surajit Dasgupta retweeted
we all want to and need to be prepared to train our own large-scale language models from scratch. why? 1. transparency or lack thereof 2. maintainability or lack thereof 3. compliance or lack thereof and because we can, thanks to amazing open-source and open-platform…
Surajit Dasgupta retweeted
Introducing ReSearch: An iterative self-reflection algorithm that enhances LLM's self-restraint abilities: • Encouraging abstention when uncertain • Producing accurate, informative content when confident Result: Significant accuracy boost for Llama2 7B Chat and Mistral 7B! 🚀
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