Shambhavi Mishra

PhD @etsmtl | Prev: Visiting Researcher @ServiceNowRSRCH | Organizer: Computer Vision Talks : @talks_cv

[Shambhavi Mishra @ShambhaviCodes]

Late Announcement : This work got accepted at TMLR 🎉
Check it out - https://t.co/LNhqb1yHw4
@TmlrOrg @TmlrPub

[Shambhavi Mishra @ShambhaviCodes]

(1/5) 🎉We've just released our latest research paper "Do not trust what you trust: Miscalibration in Semi-supervised Learning". 📈 In our study, we've made significant observations revealing intrinsic properties of semi-supervised methods built on pseudo-label generation.

[Xiuyu Li @sheriyuo]

This is exceptionally well-written. If you’re into RL, definitely give it a read

[Shambhavi Mishra @ShambhaviCodes]

@talks_cv

[Shambhavi Mishra @ShambhaviCodes]

Takeru Miyato presents AKOrN, ICLR 2025 Oral! What happens when you replace static activations with coupled oscillators governed by Kuramoto dynamics? Unsupervised object discovery, Sudoku reasoning, adversarial robustness & calibrated uncertainty - all from one framework.

[Shambhavi Mishra @ShambhaviCodes]

📅 Mar 28 | 11 AM ET 📄 https://t.co/u1LvhRpQSN🔗 https://t.co/XUAPr1U2gj
Sign up for the link: https://t.co/tLLDs1aC9s

[Chris Barber (in SF) @chrisbarber]

I made an unofficial NeurIPS 2025 hiring list:

@rronak_, @QuantumArjun, @michaelelabd, stealth, I’m a small investor: RL post-training from live product usage. Research Engineers.
@jonsid, Turing: data for frontier models. Research Engineers, SWEs.
@schwarzjn_, ICL & Thomson Reuters: LLMs for law. Research Engineers, SWEs, PhD students.
@panda_liyin, AdaL: copilot for ML engineering. MLEs, SWEs.
@sarwal_varuni, TriFetch: data and post-training for medical AI.
@bidhan, Bagel Labs: decentralized training for diffusion models. MLEs, ML Scientists.
@meggmcnulty, Cosmic Labs: AI-native OS for embedded engineering. MLEs, SWEs, systems engineers.
@samuelekpe, GrupaAI: operating system for AI agents. SWEs.
@jaradcannon, Humanoid: industrial humanoids. SWEs and applied researchers.
@saurabh_here1, Cantina: AI native social media. Research interns for video gen.
@RicardoMonti9, DatologyAI: frontier data curation (filtering, mixing, synthetic) for LLMs. Research Scientists, MLEs, SWEs.
@NimaGard, Path Robotics: physical AI to automate manufacturing tasks (e.g. welding). MLEs for robot learning.
@DrJimFan, Nvidia robotics team. Research Engineers, SWEs.
@katherine1ee, OpenAI pretraining safety team. Research Engineers.
@BorisMPower, OpenAI applied AI research team. Research Engineers.
@j_asminewang, OpenAI alignment team. Research Engineers, Research Scientists.
@zijianwang30, MSL data research team. Research Engineers, Research Scientists.
@RuiqiGao, Google DeepMind video gen team. Research Engineers, Research Scientists.
@joshim5, Chai Discovery: molecule prediction for drug discovery. Research Engineers, SWEs.
@crisbodnar, Project Prometheus: AI for manufacturing and logistics. Research Engineers.
@vdbergrianne, Microsoft Research Amsterdam materials science team. Research Engineers.
@kamath_sutra, Smallest: AI for call centers. SWEs.
@idavidrein, METR: frontier model evaluation. Research Engineer.
@jimmysmith1919, Liquid AI: on-device models. MLEs, Research Engineers.
@alxndrdavies, AI Security Institute: red-teaming. Research Scientists/Engineers.
@stuhlmueller, Elicit: AI for scientific research and good reasoning. MLEs, SWEs.
@gavincrooks, @FarisSbahi, Normal Computing: physics-based ASICs. Research Engineers, SWEs.
@myra_deng, Goodfire AI: interpretability research. Research Engineers, Research Scientists, MLEs.
@_lychrel, @SergeiIakhnin, @ja_kirkpatrick, @sbos, Isomorphic Labs: AI-first drug discovery. Research Engineers, Research Scientists, MLEs.
@kdqg1, @bneyshabur, Anthropic AI Scientist team. Research Engineers with infra experience.
@sarahookr, Adaption: continuous learning. Research Engineers.
@francedot, Cua, I’m a small investor: infra for computer-use agents. SWEs, Research Engineers.
@iScienceLuvr, Sophont: multimodal models for healthcare. Research Engineers/Research Scientists.
@aditshah00, Until Labs: organ preservation. MLEs.
@RitvikKapila & @gauri__gupta, NeoSigma: evals and post-training for real world agents. SWEs.
@abeirami, stealth: reliability & statistical evaluation. Research Engineers & SWEs.
@adityachinchure, Ideogram: image generation. Research Engineers.
@AndrewLBeam, @kenneth0stanley, Lila Sciences: autonomous labs, verifiability for science. Research Engineers, MLEs.
@brianwilt, Waymo: ML infra for motion planning team. Senior SWEs.
@thisismadani, Profluent Bio: protein generation for drug development. MLEs.

[Shambhavi Mishra @ShambhaviCodes]

Thrilled that our paper “Do not trust what you trust: Miscalibration in Semi-Supervised Learning” received the Outstanding Paper Award at #MLRC2025. Grateful to the committee and mentors! 🙏
#MachineLearning #TrustworthyAI #Calibration

[Shambhavi Mishra @ShambhaviCodes]

🚀 @talks_cv | July 5, 9:30 AM EDT
Latent Mamba Operator for PDEs [ICML'25]
📄 Neural operators meet state-space models! Learn how LaMO achieves 32.3% improvement on complex PDEs.
Speaker: Karn Tiwari, @iiscbangalore
Paper: https://t.co/8HCtNhlPR5
Join: https://t.co/0lNTQZJzN2

[Akshay 🚀 @akshay_pachaar]

KV caching in LLMs, clearly explained (with visuals):

[Lilian Weng @lilianweng]

Giving your models more time to think before prediction, like via smart decoding, chain-of-thoughts reasoning, latent thoughts, etc, turns out to be quite effective for unblocking the next level of intelligence.

New post is here :)

“Why we think”: https://t.co/21xduoZaAF

[Sai Rajeswar @RajeswarSai]

Congrats @TianbaoX and team on this exciting work and release! 🎉 We’re happy to share that Jedi-7B performs on par with UI-Tars-72B agent on our challenging UI-Vision benchmark, with 10x fewer parameters! 👏 Incredible
🤗Dataset: https://t.co/yjYkicWipc
🌐https://t.co/ArAeloOwLf

[Shambhavi Mishra @ShambhaviCodes]

Don’t miss our @talks_cv with @dem_fier from @Mila_Quebec on April 5 at 10 AM ET (30 minutes to go)! He’ll share how his team leverages #LLMs to automate the entire literature review process. Learn how #AI is reshaping academic research!
Join us : https://t.co/7Xc4R0XmUY

[Gaurav Sahu @dem_fier]

🚀 Exciting news! Our work LitLLM has been accepted in TMLR! LitLLM helps researchers write literature reviews by combining keyword+embedding-based search, and LLM-powered reasoning to find relevant papers and generate high-quality reviews.
https://t.co/ledPN4jEmP
🧵 (1/5)

[Vision Language Talks @talks_cv]

We’re renaming our reading group to VLT Reading Group to reflect our focus on vision, learning, and theory. 🎯 Stay tuned for cutting-edge AI/ML talks, research discussions, and community updates! 📢

#AI #MachineLearning #ComputerVision #DeepLearning

[Vision Language Talks @talks_cv]

Join us for a fascinating talk by Rajat Modi (PhD, @UCFCRCV) on making GLOM work with Asynchronous Perception Machines (APMs).
🗓 Date: March 15, 2025
⏰ Time: 10:00 AM EST | 7:30 PM IST
🔗 Join here: https://t.co/GjIWVVSPqV
#ComputerVision #MachineLearning #DeepLearning

[Estefanía Talavera @eTalaveraM]

I have an open PhD position on Multimodal Learning and Computer Vision. It will be under my supervision! 💫

The position is available until 19th of January to apply under https://t.co/tLYgCTDwHr

[Shambhavi Mishra @ShambhaviCodes]

Entertainment watch :

https://t.co/UTUP3zUw97

[Minhyuk Sung @MinhyukSung]

#DiffusionModels
🎓 Our "Diffusion Models and Their Applications" course is now fully available! It includes all the lecture slides, recordings, and hands-on programming assignments. Hope it helps anyone studying diffusion models.
🌐 https://t.co/LRZPwLulHw

[David Picard @david_picard]

I made a notebook with a few notes on Diffusion Models for a "tutorial" in a project-workshop yesterday. Not really an introduction, but I give some insights that I usually don't see elsewhere. Feel free to reuse.
🔗https://t.co/rFQcXBYFac

(copy from 🦋 where I'm more often)

[Jakob Foerster @j_foerst]

Cold emails are hard and good ones can change a life. Here is my email to @NandoDF that started my career in ML (at the time I was a PM at Google) https://t.co/ILaOtGQvbD Real effort (incl feedback) went into drafting it. Thanks to @EugeneVinitsky for nudging me to put it online

[Shambhavi Mishra @ShambhaviCodes]

Why we do a PhD?
To read papers infinitely! Were RNNs All We Needed led to MAMBA led to State Space Models! Love this digging deep aspect of my work :)

Feat. Not so aesthetic work space.
#AcademicChatter #ArtificialInteligence