10/ The Efficiency Spectrum of LLMs – a comprehensive review of algorithmic advancements aimed at improving LLM efficiency.
@dair_ai
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TÜLU 2: Improved Language Models for Downstream Task Adaptation
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10/ TÜLU 2 – presents a suite of improved TÜLU models for advancing the understanding and best practices of adapting pretrained language models to downstream tasks and user preferences.
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LLMs as Collaborative Agents for Medical Reasoning
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9/ LLMs as Collaborators for Medical Reasoning – proposes a collaborative multi-round framework for the medical domain that leverages role-playing LLM-based agents to enhance LLM proficiency and reasoning capabilities.
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GAIA: Benchmark for General AI Assistants Capabilities
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8/ GAIA – a benchmark for general AI assistants consisting of real-world questions that require a set of fundamental abilities such as reasoning, multimodal handling, web browsing, and generally tool-use proficiency.
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Chain-of-Thought Reasoning and Language Agents Guide
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7/ The Hitchhiker’s Guide From Chain-of-Thought Reasoning to Language Agents – summary of CoT reasoning, foundational mechanics underpinning CoT techniques, and their application to language agent frameworks.
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GPQA Benchmark Tests Graduate-Level AI Knowledge Across Sciences
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6/ GPQA – a graduate-level Google-proof QA benchmark consisting of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry; the strongest GPT-4 based baseline achieves 39% accuracy.
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Teaching Small Language Models Reasoning Techniques
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5/ Teaching Small LMs To Reason – an approach to teach smaller language models to reason; specifically, the LM is thought to use reasoning techniques, such as step-by-step processing, recall-then-generate, recall-reason-generate, extract-generate,…
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System 2 Attention: LLM Reasoning for Selective Context Processing
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1/ System 2 Attention – leverages the reasoning capabilities of LLMs to decide what to attend to; it regenerates input context to only include relevant portions before attending to the regenerated context to elicit the final response from the model.
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Top ML Papers: Mirasol3B, System 2 Attention, Speculative Sampling
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Top ML Papers of the Week (Nov 20 – Nov 26): – Mirasol3B
– System 2 Attention
– Parallel Speculative Sampling
– Advancing Long-Context LLMs
– Teaching Small LMs To Reason
– LLMs as Collaborators for Medical Reasoning
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LLM Trading Agent Hides Insider Trading Decisions
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10/ LLMs can Deceive Users – explores the use of an autonomous stock trading agent powered by LLMs; finds that the agent acts upon insider tips and hides the reason behind the trading decision.