6). Consistency LLMs – uses efficient parallel decoders that reduce inference latency by decoding n-token sequence per inference step; inspired by he human's ability to form complete sentences before articulating word by word…
@dair_ai
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DrEureka Automates Sim-to-Real Robot Design Using LLMs
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5). DrEureka – uses LLMs to automate and accelerate sim-to-real design; it requires the physics simulation for the target task and automatically constructs reward functions and domain randomization distributions to support real-world transfer…https://t.co/4k5bHESjbD
— DAIR.AI (@dair_ai) 12 mai 20245). DrEureka – uses LLMs to automate and accelerate sim-to-real design; it requires the physics simulation for the target task and automatically constructs reward functions and domain randomization distributions to support real-world transfer…
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DeepSeek-V2: 236B MoE Model with Efficient Latent Attention
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3). DeepSeek-V2 – a strong MoE 236B parameter model, of which 21B are activated for each token; supports a context length of 128K tokens and uses Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache into a latent vector…
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xLSTM Scales LSTMs to Billions Parameters with Modern LLM Techniques
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2). xLSTM – attempts to scale LSTMs to billions of parameters using techniques from modern LLMs; to enable LSTMs the ability to revise storage decisions, they introduce exponential gating and a new memory mixing mechanism…
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AlphaMath Zero: MCTS Enhances LLM Mathematical Reasoning
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4). AlphaMath Almost Zero – enhances LLMs with Monte Carlo Tree Search (MCTS) to improve mathematical reasoning capabilities; the MCTS framework extends the LLM to achieve a more effective balance between exploration and exploitation…
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AlphaFold 3 Predicts Protein DNA RNA Molecular Structures
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1). AlphaFold 3 – releases a new state-of-the-art model for accurately predicting the structure and interactions of molecules; it can generate the 3D structures of proteins, DNA, RNA, and smaller molecules…https://t.co/avOFMTnTwz
— DAIR.AI (@dair_ai) 12 mai 20241). AlphaFold 3 – releases a new state-of-the-art model for accurately predicting the structure and interactions of molecules; it can generate the 3D structures of proteins, DNA, RNA, and smaller molecules…
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Top ML Papers Week May 6-12 xLSTM AlphaFold DeepSeek
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The Top ML Papers of the Week (May 6 – May 12): – xLSTM
– DrEureka
– AlphaFold 3
– DeepSeek-V2
– Consistency LLMs
– AlphaMath Almost Zero
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Multimodal LLM Hallucinations: Advances in Detection and Mitigation
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9). Multimodal LLM Hallucinations – provides an overview of the recent advances in identifying, evaluating, and mitigating hallucination in multimodal LLMs.
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In-Context Learning Performance with Extreme Long-Context Models
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10). In-Context Learning with Long-Context Models – studies the behavior in-context learning of LLMs at extreme context lengths with long-context models; shows that performance increases as hundreds or thousands of demonstrations are used.
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Interpreting Transformer Language Models: Technical Deep Dive
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8). Inner Workings of Transformer Language Models – presents a technical introduction to current techniques used to interpret the inner workings of Transformer-based language models.