Improving Text Embeddings with Large Language Models: Training Post date March 1, 2025 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Holistic Evaluation of Text-to-Image Models: Human evaluation procedure Post date October 13, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
A Deep Dive Into Stable Diffusion and Other Leading Text-to-Image Models Post date October 13, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Human vs. Machine: Evaluating AI-Generated Images Through Human and Automated Metrics Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
From Birdwatching to Fairness in Image Generation Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Holistic Evaluation of Text-to-Image Models: Datasheet Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Holistic Evaluation of Text-to-Image Models: Author contributions, Acknowledgments and References Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Limitations in AI Model Evaluation: Bias, Efficiency, and Human Judgment Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Paving the Way for Better AI Models: Insights from HEIM’s 12-Aspect Benchmark Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
New Dimensions in Text-to-Image Model Evaluation Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Photorealism, Bias, and Beyond: Results from Evaluating 26 Text-to-Image Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, hackernoon-top-story, heim-benchmark, multilingual-ai-models, text-to-image-models, zero-shot-prompting
A Comprehensive Evaluation of 26 State-of-the-Art Text-to-Image Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Evaluating AI Models with HEIM Metrics for Fairness, Robustness, and More Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Curating 62 Practical Scenarios to Test AI Text-to-Image Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
12 Key Aspects for Assessing the Power of Text-to-Image Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
HEIM’s Core Framework: A Comprehensive Approach to Text-to-Image Model Assessment Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Holistic Evaluation of Text-to-Image Models Post date October 12, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-bias, ai-evaluation-framework, ai-model-fairness, heim-benchmark, multilingual-ai-models, prompt-engineering, text-to-image-models, zero-shot-prompting
Improving Text Embeddings with Large Language Models: Instructions for Training and Evaluation Post date October 10, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Prompts for Synthetic Data Generation Post date October 10, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Implementation Details Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Conclusion and References Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Analysis of Training Hyperparameters Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Is Contrastive Pre-training Necessary? Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Multilingual Retrieval Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Main Results Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Model Fine-tuning and Evaluation Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Statistics of the Synthetic Data Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
Improving Text Embeddings with Large Language Models: Synthetic Data Generation Post date October 9, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In ai-for-information-retrieval, beir-benchmark, contrastive-pre-training, language-models, multilingual-ai, natural-language-processing, synthetic-data-generation, text-embeddings
CulturaX: A High-Quality, Multilingual Dataset for LLMs – Conclusion and References Post date August 28, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In data-cleaning, dataset-creation, large-language-models, multilingual-learning, multilingual-llms, natural-language-processing, open-source-data, text-deduplication
CulturaX: A High-Quality, Multilingual Dataset for LLMs – Related Work Post date August 28, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In data-cleaning, dataset-creation, large-language-models, multilingual-learning, multilingual-llms, natural-language-processing, open-source-data, text-deduplication
CulturaX: A High-Quality, Multilingual Dataset for LLMs – Data Analysis and Experiments Post date August 28, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In data-cleaning, dataset-creation, large-language-models, multilingual-learning, multilingual-llms, natural-language-processing, open-source-data, text-deduplication
CulturaX: A High-Quality, Multilingual Dataset for LLMs – Multilingual Dataset Creation Post date August 28, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In data-cleaning, dataset-creation, large-language-models, multilingual-learning, multilingual-llms, natural-language-processing, open-source-data, text-deduplication
CulturaX: A High-Quality, Multilingual Dataset for LLMs – Abstract and Introduction Post date August 28, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In data-cleaning, dataset-creation, large-language-models, multilingual-learning, multilingual-llms, natural-language-processing, open-source-data, text-deduplication
NExT-GPT: Any-to-Any Multimodal LLM: Instruction Tuning Post date July 31, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In any-to-any-mm-llms, artificial-intelligence, diffusion-decoders, large-language-models, mm-llms, mosit, multimodal-adaptors, next-gpt
NExT-GPT: Any-to-Any Multimodal LLM: Abstract and Intro Post date July 31, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In any-to-any-mm-llms, artificial-intelligence, diffusion-decoders, large-language-models, mm-llms, mosit, multimodal-adaptors, next-gpt
Simplifying Transformer Blocks: Implementation Details Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Simplifying Transformer Blocks: Additional Experiments Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Simplifying Transformer Blocks: Block Layouts Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
A Duality Between Downweighted Residual and Restricting Updates In Linear Layers Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Simplifying Transformer Models for Faster Training and Better Performance Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Improving Training Stability in Deep Transformers: Pre-LN vs. Post-LN Blocks Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Simplifying Transformer Blocks: Related Work Post date June 19, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture, transformer-efficiency
Simplifying Transformer Blocks without Sacrificing Efficiency Post date June 18, 2024 Post author By Auto Encoder: How to Ignore the Signal Noise Post categories In deep-learning, deep-transformers, hackernoon-top-story, neural-network-architecture, neural-network-efficiency, signal-propagation-theory, simplified-transformer-blocks, transformer-architecture
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