7. AdaptThink This paper introduces AdaptThink, an RL framework designed to help reasoning models decide when to use detailed chain-of-thought reasoning (“Thinking”) versus directly producing an answer (“NoThinking”), based on task difficulty.
MACHINE LEARNING
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LLM Reasoning in Dynamic Environments Beyond Static Benchmarks
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6. Towards a Deeper Understanding of Reasoning in LLMs This paper investigates whether LLMs can adapt and reason in dynamic environments, moving beyond static benchmarks.
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AI Model Predicts Immunotherapy Treatment Response Outcomes
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5. AI Predicts Immunotherapy Outcomes Across Cancers and Treatments Introduces COMPASS, a concept bottleneck-based foundation model that predicts patient response to immune checkpoint inhibitors (ICIs) using tumor transcriptomic data.
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Chain-of-Thought Prompting Trade-offs in Reasoning Models
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4. The Pitfalls of Reasoning Explores an unexpected flaw in reasoning-augmented large language models (RLLMs): while chain-of-thought (CoT) prompting often boosts performance on complex reasoning tasks, it can degrade instruction-following accuracy.
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EfficientLLM: Benchmark for LLM efficiency trade-offs
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2. EfficientLLM Introduces the first large-scale, empirical benchmark for evaluating efficiency trade-offs in LLMs across architecture, fine-tuning, and inference.
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Top AI Research Papers of the Week: May 19-25
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Here are the top AI Papers of the Week (May 19 – 25): – ARC-AGI-2
– AdaptThink
– EfficientLLM
– Visual Planning
– The Pitfalls of Reasoning
– Teaching MLLMs to Think with Images Here is the full list: -
Visual Planning: Image-Based Reasoning Replaces Language Planning
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1. Visual Planning Proposes a novel reasoning paradigm that replaces language-based planning with image-based reasoning.
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AI Agent Progression Framework: 5 Levels of Evolution
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AI Agent Progression Framework: 5 Levels of Evolution
Want to know where your AI system stands? Here's a breakdown: Rule-based Automation: If-then logic, no learning Intelligent Automation: Basic ML, limited autonomy Agentic Workflows: Tools + reasoning + language -
Two AI Minds Share Insights on LLMs and Agents
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Written by two of my favorite minds in the #AI space: @maartengr and @JayAlammar If you found this useful, a like or RT is always appreciated! Follow me → @datachaz for insights on LLMs, AI agents, and data science!
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Hands-On Large Language Models GitHub Repository
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here's the repo link:
↳ https://
github.com/HandsOnLLM/Han
ds-On-Large-Language-Models?tab=readme-ov-file
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