Training Strategies for Efficient Embodied Reasoning https://arxiv.org/abs/2505.08243 The ability of robotic policies to generalize is crucial for their application in various scenarios. Currently, the training of robotic policies often relies on a large amount of robotic experience data, which is typically collected through manual remote control, leading to high costs and low efficiency. VLA enhances … Read more
Hello everyone, today I bring you analogy questions from the reasoning module. These not only test the breadth of our knowledge but also our ability to summarize and inductively reason. Let’s practice together: Question （ ） is to car as （ ） is to camera A. Tire ； Mobile phone B. Speed ； Pixel C. … Read more
Hello everyone, today I bring you a question from the reasoning module regarding analogies. This not only tests our breadth of knowledge but also our ability to summarize and inductively reason. Let’s practice together: QuestionUncleNephew∶Relationship∶Blood Relation A. Galaxy∶Star∶Universe B. Aunt∶Sister-in-law∶Family C. Classroom∶Knowledge∶Textbook D. Depression∶Disease∶Psychology Answer#01 [Answer] D [Analysis] This question belongs to the category of … Read more
1. Overview of Operators Operators are symbols used in the C language to perform various operations, and they are the basic elements that make up expressions. C provides a rich variety of operator types that can perform arithmetic operations, relational comparisons, logical evaluations, bit manipulations, and more. Mastering the use of operators is an important … Read more
Core Issues: Limitations of Existing Methods: Current large language model (LLM) agent frameworks and inference-time algorithms often struggle with complex planning problems. Main Reasons: Insufficient Validation: Many methods find it difficult to effectively validate whether the generated plans meet all constraints or only perform coarse validation at the task level. Poor Complexity Adaptability: Existing methods … Read more
Since the launch of ChatGPT, many first-wave generative AI applications have emerged as variants of chat systems using Retrieval-Augmented Generation (RAG) models on document corpora. While significant efforts are being made to enhance the robustness of RAG systems, different teams are beginning to construct the next generation of AI applications, focusing on a common theme: … Read more
© Author | Wen Jiaxin Affiliation | Master’s Student at Tsinghua UniversityWhat form should large models take for inference? Is natural language the best way to represent the reasoning path?In September 2024, OpenAI sounded the horn for a reasoning revolution with the o1 model, refreshing cognitive boundaries with astonishing chain lengths of thought. In this … Read more
New Intelligence Report Editor: LRS [New Intelligence Guide] Enabling language models to think like humans. When ChatGPT was first released, it shocked us with its performance in conversations, so much so that it created the illusion that language models possess “thinking abilities”. However, as researchers delved deeper into language models, they gradually discovered that there … Read more
One Basic Analysis of Logical Reasoning The number of logical reasoning questions remains stable at 40 each year, divided into graphic reasoning, definitional judgment, analogical reasoning, and logical judgment, with 10 questions for each type. Two Key Question Type Analysis 01 Graphic Reasoning The graphic reasoning section covers a wide range of topics, mainly including … Read more