Large Concept Models: Language Modeling in a Sentence Representation Space | #ai #2024 #genai
AI Today6 Jan 2025

Large Concept Models: Language Modeling in a Sentence Representation Space | #ai #2024 #genai

Paper: https://scontent-dfw5-1.xx.fbcdn.net/... This research paper introduces Large Concept Models (LCMs), a novel approach to language modeling that operates on sentence embeddings instead of individual tokens. LCMs aim to mimic human-like abstract reasoning by processing information at a higher semantic level, enabling improved handling of long-form text generation and zero-shot multilingual capabilities. The authors explore various LCM architectures, including MSE regression, diffusion-based generation, and quantized models, evaluating their performance on summarization, summary expansion, and cross-lingual tasks. The study demonstrates that diffusion-based LCMs outperform other methods, exhibiting impressive zero-shot generalization across multiple languages. Finally, the authors propose extending the LCM framework with a high-level planning model to further enhance coherence in long-form text generation. #ai, #artificialintelligence, #arxiv, #research, #paper, #publication, #llm, #genai, #generativeai, #largevisualmodels, #largelanguagemodels, #largemultimodalmodels, #nlp, #text, #machinelearning, #ml, #nvidia, #openai, #anthropic, #microsoft, #google, #technology, #cuttingedge, #meta, #llama, #chatgpt, #gpt, #elonmusk, #samaltman, #deployment, #engineering, #scholar, #science, #apple, #samsung, #turing, #aiethics, #innovation, #futuretech, #deeplearning, #datascience, #computervision, #autonomoussystems, #robotics, #dataprivacy, #cybersecurity, #digitaltransformation, #quantumcomputing, #aiapplications, #aiethics, #techleadership, #technews, #aiinsights, #aiindustry, #aiadvancements, #futureai, #airesearchers

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Mixtures of In-Context Learners | #ai #genai #llm #2024 #ml

Mixtures of In-Context Learners | #ai #genai #llm #2024 #ml

Paper: https://arxiv.org/pdf/2411.02830 This research introduces Mixtures of In-Context Learners (MOICL), a novel approach to improve in-context learning (ICL) in large language models (LLMs). MOICL ...

27 Nov 202414min

LLM2CLIP: POWERFUL LM UNLOCKS RICHER VISUAL REPRESENTATION | #ai #genai #lvm #llm #mmm #cv #ms #2024

LLM2CLIP: POWERFUL LM UNLOCKS RICHER VISUAL REPRESENTATION | #ai #genai #lvm #llm #mmm #cv #ms #2024

Paper: https://arxiv.org/pdf/2411.04997 Github: https://github.com/microsoft/LLM2CLIP The paper introduces LLM2CLIP, a method to improve the visual representation learning capabilities of CLIP by int...

27 Nov 202414min

OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024

OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024

Paper: https://arxiv.org/pdf/2411.14199 Github: https://github.com/AkariAsai/OpenScholar The research introduces OpenScholar, a retrieval-augmented large language model (LLM) designed for synthesizin...

27 Nov 202414min

Bilateral Reference for High-Resolution Dichotomous Image Segmentation | #ai #genai #llm #cv #2024

Bilateral Reference for High-Resolution Dichotomous Image Segmentation | #ai #genai #llm #cv #2024

Paper: https://arxiv.org/pdf/2401.03407 Github: https://github.com/ZhengPeng7/BiRefNet This research introduces BiRefNet, a novel deep learning framework for high-resolution dichotomous image segment...

27 Nov 202414min

LLaVA-o1: Let Vision Language Models Reason Step-by-Step | #ai #genai #lvm #llm #mmm #cv #2024

LLaVA-o1: Let Vision Language Models Reason Step-by-Step | #ai #genai #lvm #llm #mmm #cv #2024

Paper: https://arxiv.org/pdf/2411.10440 Github: https://github.com/PKU-YuanGroup/LLaV... The paper introduces LLaVA-o1, a vision-language model designed for improved multi-stage reasoning. Unlike pre...

27 Nov 202414min

Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024

Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024

Paper: https://arxiv.org/pdf/2408.04498 This research introduces Model-Based Transfer Learning (MBTL), a novel framework for improving the efficiency and robustness of deep reinforcement learning (RL...

27 Nov 202414min

Diverse and Effective Red Teaming Auto-gen Rewards & Multi-step RL | #aisafety #openai #genai #2024

Diverse and Effective Red Teaming Auto-gen Rewards & Multi-step RL | #aisafety #openai #genai #2024

Paper: https://cdn.openai.com/papers/diverse... Blog: https://openai.com/index/advancing-re... This OpenAI research paper presents novel methods for automated red teaming of large language models (LL...

27 Nov 202414min

OpenAI’s Approach to External Red Teaming for AI Models and System | #aisafety #openai #genai #2024

OpenAI’s Approach to External Red Teaming for AI Models and System | #aisafety #openai #genai #2024

Paper: https://cdn.openai.com/papers/openais... Blog: https://openai.com/index/advancing-re... This white paper details OpenAI's approach to external red teaming for AI models and systems. External r...

27 Nov 202414min

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