Alternatives and similar repositories for MultiModN

Users that are interested in MultiModN are comparing it to the libraries listed below

• PKU-ML / non_neg
  Official Code for ICLR 2024 Paper: Non-negative Contrastive Learning
  ☆45Updated last year
• lapisrocks / DiscreteAdversarialDistillation
  [NeurIPS 2023] Official repository for "Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models"
  ☆12Updated last year
• kalelpark / RAL
  [ICCVW2023] Robust Asymmetric Loss for Multi-Label Long-Tailed Learning
  ☆18Updated last year
• uclaml / MoE
  Towards Understanding the Mixture-of-Experts Layer in Deep Learning
  ☆31Updated last year
• badripatro / mamba360
  State Space Models
  ☆68Updated last year
• ExplainableML / fomo_in_flux
  Code and benchmark for the paper: "A Practitioner's Guide to Continual Multimodal Pretraining" [NeurIPS'24]
  ☆57Updated 7 months ago
• divyam3897 / I2M2
  I2M2: Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning (NeurIPS 2024)
  ☆20Updated 8 months ago
• pliang279 / FactorCL
  [NeurIPS 2023] Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
  ☆69Updated last year
• eth-medical-ai-lab / Med-PRM
  Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards
  ☆35Updated 3 weeks ago
• pliang279 / MultiViz
  [ICLR 2023] MultiViz: Towards Visualizing and Understanding Multimodal Models
  ☆96Updated 10 months ago
• james-oldfield / muMoE
  [NeurIPS'24] Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
  ☆33Updated 9 months ago
• AITRICS / Medical_Tri_Modal_Pilot
  Medical multi-modal learning with missing modality data (MLHC 2023)
  ☆13Updated last year
• bwconrad / soft-moe
  PyTorch implementation of "From Sparse to Soft Mixtures of Experts"
  ☆58Updated last year
• sczzz3 / EHRDiff
  An offical implementation of EHRDiff [TMLR]
  ☆25Updated last year
• dustn1259 / EHRCon
  Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records
  ☆22Updated 10 months ago
• tum-ai / number-token-loss
  A regression-alike loss to improve numerical reasoning in language models
  ☆18Updated last month
• pliang279 / HighMMT
  [TMLR 2022] High-Modality Multimodal Transformer
  ☆116Updated 8 months ago
• JxuanC / MindGPT
  Official repo for MindGPT
  ☆32Updated last year
• OpenNLPLab / HGRN2
  HGRN2: Gated Linear RNNs with State Expansion
  ☆55Updated 10 months ago
• fistyee / MixPro
  🔥MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer [Official, ICLR 2023]
  ☆21Updated last year
• facebookresearch / ModelRatatouille
  Recycling diverse models
  ☆45Updated 2 years ago
• pliang279 / PID
  [NeurIPS 2023, ICMI 2023] Quantifying & Modeling Multimodal Interactions
  ☆77Updated 8 months ago
• rajesh-lab / symile
  Symile is a flexible, architecture-agnostic contrastive loss that enables training modality-specific representations for any number of mo…
  ☆36Updated 3 months ago
• canyuchen / ClinicalBench
  Code for the paper "ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?"
  ☆18Updated 3 weeks ago
• UCSC-VLAA / o1_medical
  ☆48Updated 4 months ago
• alextamkin / active-learning-pretrained-models
  Active Learning Helps Pretrained Models Learn the Intended Task (https://arxiv.org/abs/2204.08491) by Alex Tamkin, Dat Nguyen, Salil Desh…
  ☆11Updated 2 years ago
• jyansir / tp-berta
  [ICLR 2024 spotlight] Making Pre-trained Language Models Great on Tabular Prediction
  ☆56Updated last year
• Stanford-AIMI / RaVL
  [NeurIPS 2024] RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
  ☆24Updated 8 months ago
• csinva / tree-prompt
  Tree prompting: easy-to-use scikit-learn interface for improved prompting.
  ☆38Updated last year
• wangxu0820 / NegativePrompt
  The official GitHub page for paper "NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional St…
  ☆23Updated last year