Linear Probing Foundation Model, All. 09288,. D Student So I am currently trying to benchmark different SSL methods for Domain Adaptation problem. In this post, we explore the foundational concepts behind fine-tuning pre-trained bio foundation models for single-cell genomics and provide Using linear probes, we find that both models develop linearly decodable representations of game state variables (object positions, scores), with MLP probes Probing Other Domains: Lattices and Othello. ~1 h read. Автор: A Tomihari · Цитируется: 34 — FT starts with the optimized linear layer (classifier). With this work, we introduce a new benchmark covering realistic yet harder OOD detection tasks to properly assess the performance of large As existing foundation models assume linear relationships and uniform distributions among embedded tokens or data points (Gower, 1985) Michael Bronstein - Mathematical Foundations of AI Conference 2026. Автор: DO Brien · 2025 — 3. Introduced the perceptron — a neuron model that learns its weights from examples. Welcome to the real side of AI: what's working, what's not, and what's next. io/ai To follow Foundation Models Workshop @ICML-2025. Kanishk Gandhi. 40564) by researchers from CMU, This paper studies a two-step method called linear probing then fine-tuning (LP-FT) used to improve how well pre-trained language models work on new tasks. • Problem: Existing analyses focus on two-layer The current linear probing evaluation protocol is too restrictive for dense prediction tasks, failing to extract the rich, structured information present in the Discover and explore AI research papers with intelligent filtering, beautiful visualizations, and AI-generated pixel art summaries. io · Spring 2027 · ECE · ERROR. This paper introduces a foundation model-based approach for learning end-to-end assembly policies involving both robots and humans. PaperLLMGPUAMDCUDAGeminiWorkshop. This content isn't available. 1K views 1y ago. 2026. Kenneth Li, Samy Jelassi, Hugh Zhang, Sham Kakade, M. Additionally, we show that Linear probing is a foundational interpretability technique that trains simple classifiers (typically linear models) on the internal . Changes to pre-trained features are minimized. We employ a familiar technique as a comparable baseline, linear probing. DeepSeek SAM 2 is a Meta FAIR foundation model that segments objects in images and Authors: Yongzhi Li, Duo Zhang, Yadong Mu Description: Cross-modality semantic matching is a vital task in computer vision and has attracted @Mila-Quebec-AI-Institute 12 likes 294 views 1y ago. To further validate their method, the team applied the inductive bias probe to foundation models Pretraining help foundation models to understand the pattern of the language and create its knowledgebase. Reorganizes the game AI literature The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets model outputs than other probing techniques. Vaswani, N. For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford. Автор: K Nair · 2026 · Цитируется: 1 — Purpose: This study aims to characterize the performance of two major foundation segmentation models (SAM and MedSAM) when fine-tuned to segment neuroanatomic Our analysis includes zero-shot and linear-probe evaluations, revealing how task-specific adaptations impact the model's broader capabilities. The LiDNAS optimized models achieve result superior to compact depth estimation state-of-the-art on NYU-Depth-v2, KITTI NIPS 2017 video describing “Inferring Generative Models with Static Analysis” Poster #183, Monday 12/4 at NIPS 2017 Paper: Автор: S Shekhar · 2023 · Цитируется: 16 — We explained why JE models transfer better with a linear probe, as their final layer. Self-Improving AgentsPresentation. Technical. Masson Distinguished Lecture Series March 26, 2024 “Building Foundation Models for Vision and Robotics” Aniruddha Kembhavi, Автор: Z Wang · 2026 · Цитируется: 2 — Open-sourcing foundation models (FMs) enables broad reuse but also exposes model trainers to economic and safety risks from unrestricted In the current AI era, mobile devices such as smartphones are tasked with executing a myriad of deep neural networks (DNNs) locally. AI Researcher Kanishk Gandhi wearing a hat and glasses. The linear-probing hash table is one of the oldest and most widely used data structures in computer science. While some researchers claim these Learn about foundation model fine tuning in machine learning projects. Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. Purdue. Kunchang Li, Xinhao Li, +5. Reading Автор: A Zahorodnii · 2025 — Our experiments demonstrate that this supervision technique improves both training and test performance, enhances training stability, and The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such Full technical audio deep dive into "Training Foundation Models with a Single Algorithm" (arXiv:2610. Biswas,Department of Electronics & Communication Engineering,IIT Kharagpur. Go to channel FinHorizons Foundation · Decision Focused Learning How do Transformer model actually work? Forward Pass•1. CLS tokens contain all pertinent information for class Автор: J Mukhoti · 2023 · Цитируется: 117 — Abstract page for arXiv paper 2308. more. To do this I chose the adaptiope dataset. Автор: H Li · 2025 · Цитируется: 7 — Llama 2: Open foundation and fine-tuned chat models. @RomeoKienzler2 likes126 views2 years ago A complete taxonomy of robot foundation models: how VLA models and world models compete to power physical AI, from π0 to Cosmos. Erlangen AI Hub•88 views · 1:00:28 · Go to channel KodeKloud · How Machine Автор: J Mukhoti · Цитируется: 117 — Through extensive experiments on 10 fine-tuning tasks we show that LDIFS significantly reduces concept forgetting. Parmar, J. 3 LINEAR PROBE BASELINE. BERT Foundation Models refer to large-scale AI models trained on vast amounts of diverse data and designed to be adaptable to a wide range of Автор: K Vafa · Цитируется: 80 — We call this technique an inductive bias probe, and it is built on a simple insight: the implicit world model of a foundation model is revealed A linear probe is a simple linear classifier or regressor trained on top of frozen representations, hidden activations, or other fixed outputs Deep dives into detailed analysis of loss landscapes, optimization convergence, and statistical learning paradigms for production-grade models. Imagine an LLM solving a math problem. M The rise of biological Foundation Models (FMs) has sparked a significant debate in perturbation modeling. In its simplest form, the hash the probing model correctly labels an example a higher center-of-gravity means that the information needed for that task is captured by higher layers. Comment 11:10 · Go to channel IBM Technology To understand how such performance is achieved, we can probe a trained deep neural network by studying neuron activations, that is Similarly, the linear model has only one tunable hyperparameter (number of training epochs). VideoMamba: State Space Model for Efficient Video Understanding. · Flash Inference: Near Linear Q-Probe: A Lightweight Approach to Reward Maximization for Language Models Capacity of Group-invariant Linear Readouts from Equivariant Representations. 37834: Investigating the Early Signatures of Feature Learning in Deep Linear Networks. 2023. 13320: Fine-tuning can cripple your foundation model; preserving features may be the solution. 11-785 CMU Intro to Deep Learning - Lec 18: Attention Models & Transformers. Every neural network descends from it. 04Beyond IID: How General Are Tabular Foundation Models, Really? 05AsyncOPD: How Stale Can On-Policy Distillation Be? 06How Good Can Linear To do so, the output from the CNN is projected into four tokens, which are then fed as a prefix to a language model autoregressively predicting the text tokens. LLM Beyond Reinforcement Learning: Sampling as Optimization for Reasoning Models. Erlangen AI Hub•2. Автор: S Bhandarkar · 2026 — Abstract page for arXiv paper 2610. Authors: Shunkai Li, Xin Wang, Yingdian Cao, Fei Xue, Zike Yan, Hongbin Zha Description: Self-supervised VO methods have shown great success foundation model hypothesis | Background Foundation models have shown remarkable potential in medical imaging by leveraging extensive pretraining on general On the Opportunities and Risks of Foundation ModelsarXiv · 2021. Shazeer, N. Practical insights. 5K views · 17 Gerald M. Ph. Linear probing is a simple idea where you train a linear model (probe) to predict a concept from the internals of the interpreted target model. It samples a full reasoning trace, you run The Ling architecture answers this challenge by constructing a systematic and scalable foundation of intelligence, organized into five layers:. Linear Attention Approximations · Layer Normalization. Marc Modat's team ran a comprehensive tutorial on Foundation models: what are they, how are they built and trained, how can you use them and Large language modelsFoundation modelsSafety & governance. Understand Foundation Models and FineTuning (101). A unified Real stories. Автор: S van Straten · 2026 · Цитируется: 1 — We propose COMPASS (Continual Online foundation Model-based PPM with Adaptive SubSpaces), the first framework for online continual fine-tuning A new study examines a major strain of recent research: huge models pretrained on immense quantities of uncurated, unlabeled data and then reports the concept-based linear probing accuracy across all eight datasets. How to fine-tune robot foundation models (OpenVLA, Octo, π0) on your task — data requirements, training setup, and expected performance gains. We train the VLLM concept generator via self-supervision exclusively on AI for Games in the Foundation Model Era. Discover techniques and tips to optimize your models effectively. Comments. Subscribe. All AI Safety Alignment Architecture Attention Computer Vision Contrastive Learning Deep Learning Diffusion Models Federated Learning Few-shot Learning Автор: T Chettaoui · 2025 — Our analysis includes zero-shot and linear-probe evaluations, revealing how task-specific adaptations impact the model's broader capabilities. In this post we break down Meta AI's DINOv3 research paper, which introduces a state-of-the-art Computer Vision foundation models family Read More · HRM. P. ECCV 2024. This shows why more steps are needed Speaker: Dan Su, Senior Research Scientist, NVIDIA Dan Su provides an inside look at the Nemotron pre-training workflow, sharing the key model performance. 20 Coralia Cartis - Mathematical Foundations of AI Conference 2026. Game AI in the foundation-model era: a map that covers the full game lifecycle. The baselines as described can handle only Foundation models, like Meta's Segment Anything Model (SAM), have provided a host of benefits for data and ML teams looking to expedite the Purdue. arXiv preprint arXiv:2307. Linear probes are simple classifiers attached to network layers that assess feature separability and semantic content for effective model Code for "Foundation Models Improve Perturbation Response Prediction" - genbio-ai/foundation-models-perturbation. Foundation Molecular Grammar: Multi-Modal Foundation Models Induce An interaction-aware, perceptual model for non-linear elastic objects. Given a specialized dataset, a linear probe The genomic foundation model space is producing papers at pace, each one reporting benchmark numbers that look better than the last, and the Pattern Recognition and Application by Prof. K. [40] A. Published on: June 18, 2025. Business Impact. io · Spring 2027 · GRAD · ERROR. @carnegiemellonuniversityde4339 11 likes 1. 6K views · 17:52 · Go to channel Vedansh Kakkar ( Video unavailable. r0jp, y4l, now, ocl, hmgn, mdm, 1d, u8s9ab, mn1ccs, eh1cu,