RepICL: Reusable In-Context Prediction Across Heterogeneous Representation Spaces
cs.LG
Submitted: 2026-10-05
Updated: 2026-10-05
Code: https://github.com/sicara/easy-few-shot-learning
Sources
- MAEB: Massive Audio Embedding Benchmark
- Gemma 3 Technical Report
- The Llama 3 Herd of Models
- jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers
- Mistral 7B
- Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
- DINOv3
- Whitening Sentence Representations for Better Semantics and Faster Retrieval
- EVA-CLIP: Improved Training Techniques for CLIP at Scale
- SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
- EmbeddingGemma: Powerful and Lightweight Text Representations
- fairseq S2T: Fast Speech-to-Text Modeling with fairseq
- Text Embeddings by Weakly-Supervised Contrastive Pre-training
- SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning
- Omni-Embed-Nemotron: A Unified Multimodal Retrieval Model for Text, Image, Audio, and Video
- Qwen3 Technical Report
- Jasper and Stella: distillation of SOTA embedding models
- Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
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