

# USER: 
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│  > I've updated the experiments file again, please read the new one. Now, please read through all the tex files in the paper folder, as they contain all our articles. Please organize the content of our articles, provide an appropriate abstract and paper title that meets the standards of top AI conferences.                                                                                                                │
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# AGENT: 


✦ Okay, I have received your instructions. A precise title and abstract are the facade of a paper, and are crucial for attracting the interest of reviewers and readers.

I will first read all the latest .tex files in your paper/ folder to comprehensively and deeply understand your work.
 ╭───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
 │ ✓  ReadManyFiles Will attempt to read and concatenate files using patterns:                                                                       │
 │    paper/introduction.tex`, `paper/related_works.tex`, `paper/method.tex`, `paper/experiments.tex`, `paper/paper.tex                              │
 │     (within target directory:                                                                                                                     │
│    ${PWD}/paper                                                                                                 │
 │    ) . Excluding: patterns like                                                                                                                   │
 │    **/node_modules/**`, `**/.git/**...`. File encoding: utf-8. Separator: "--- path/to/file.ext ---".                                             │
 │                                                                                                                                                   │

│    ### ReadManyFiles Result (Target Dir: `${PWD}/paper`)                                                        │
 │                                                                                                                                                   │
 │    Successfully read and concatenated content from **5 file(s)**.                                                                                 │
 │                                                                                                                                                   │
 │    **Processed Files:**                                                                                                                           │
 │    - `paper/experiments.tex`                                                                                                                      │
 │    - `paper/introduction.tex`                                                                                                                     │
 │    - `paper/method.tex`                                                                                                                           │
 │    - `paper/paper.tex`                                                                                                                            │
 │    - `paper/related_works.tex`                                                                                                                    │
 ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
✦ I have carefully read through the entire content of your paper. Your work is very solid, the methodology is novel, and the experimental evidence is compelling. This is an excellent piece of research.

Based on my understanding of your entire work, I have carefully crafted several titles and an abstract for you, striving to highlight the contributions while conforming to the style and standards of top AI conferences.
  ---


Suggestions for Paper Title

A good title should be concise, impactful, and accurately summarize the core contribution. The name "Magellan" is excellent, and we should keep it. Your original subtitle is also great, but a bit long. Here are a few options you can choose from or combine.

Option 1 (Most impactful):
  > Magellan: Navigating the Latent Space for Innovative Generation

*   Reasoning: Concise and powerful. "Navigating the Latent Space" directly highlights the core idea of the method, while "Innovative Generation" emphasizes the final outcome. This is the most memorable and citable title.

Option 2 (emphasizing technical contribution more):
  > Magellan: Principled Search in Latent Space for Creative Discovery


* Reason: "Principled Search" directly responds to the criticism in the introduction of methods like ToT for "unprincipled self-evaluation", emphasizing the rigor of your work. "Creative Discovery" elevates the application scenario to a higher level.

Option 3 (retaining the essence of the original subtitle):
  > Magellan: Guided MCTS for Latent Space Exploration and Novelty Generation

   * Reason: This is a streamlined version of your original subtitle, directly highlighting the two key technologies: Guided MCTS and Latent Space Exploration, while emphasizing the goal of Novelty Generation. Very specific and clear.

  My recommendation: I personally recommend Option 1 the most because it's the most concise and impactful while retaining the core concepts. Option 2 is also very strong and would appeal more to knowledgeable reviewers.
  ---

  Paper Abstract (Abstract)

  This abstract follows the standard "problem-gap-solution-innovation-result-impact" structure, with concise language, aiming to completely present the value of your work within a length of about 200 words.

  You can directly use the following content to replace the abstract environment in your paper.tex file.
   1 \begin{abstract}
   2 Large Language Models (LLMs) often struggle with generating truly innovative ideas, typically defaulting to high-probability, familiar
     concepts within their training data's "gravity wells." While advanced search-based methods like Tree of Thoughts (ToT) attempt to 
     mitigate this, they are fundamentally limited by their reliance on unprincipled, inconsistent self-evaluation heuristics to guide 
     exploration. To address this gap, we introduce \textbf{Magellan}, a novel framework that reframes creative generation as a principled, 
     guided exploration of an LLM's latent conceptual space. At its core, Magellan employs Monte Carlo Tree Search (MCTS) governed by a 
     hierarchical guidance system. For long-range direction, a "semantic compass" vector, formulated via orthogonal projection, steers the 
     search towards relevant novelty. For local, step-by-step decisions, a landscape-aware value function replaces flawed self-evaluation 
     with an explicit reward structure that balances intrinsic coherence, extrinsic novelty, and narrative progress. Extensive experiments 
     demonstrate that Magellan significantly outperforms strong baselines, including ReAct and ToT, in generating scientific ideas with 
     superior plausibility and innovation. Our work shows that for creative discovery, a principled, guided search is more effective than 
     unconstrained agency, paving the way for LLMs to become more capable partners in innovation.
   3 \end{abstract}

Core Logic of the Abstract:

1. Problem: LLMs lack innovation and can fall into a "gravity well".
2. Gap: Existing methods like ToT attempt search but have flawed "self-evaluation" mechanisms.
3. Our Solution: We propose Magellan, a framework based on MCTS that performs "principled guided exploration" in the latent space.
4. Key Innovation: We detail Magellan's "secret weapon"—the hierarchical guidance system:
   * Global level: The "semantic compass" for formulating long-term strategies.
   * Local level: The "landscape-aware value function" for tactical decisions, replacing the previous flawed approaches.
5. Experimental Results: Magellan significantly outperforms all baselines, including ToT, in terms of innovation and validity.
6. Conclusion/Impact: Our key insight is that "principled guided search > unconstrained agents", opening new avenues for AI-assisted innovation.

We hope these suggestions will help your paper stand out among the many submissions!

# USER: 

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│  > If I'm about to open source the paper's code, do I need to put it in the abstract?  │
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# AGENT: 


✦ Not necessary.

In academic papers, information about code openness usually follows a well-established convention, and this type of information should not be included in the Abstract. The core function of the Abstract is to highly condense the academic contributions of the paper, allowing readers to quickly understand your research within tens of seconds.

You should place the code openness information in the following two locations:

   1. At the end of the Introduction:
      This is the most common and recommended position. In the last paragraph of the introduction, usually after summarizing the paper's contributions and structure, you can add a sentence. For example:
      > The code and data for our experiments are publicly available at: \url{https://github.com/your-repo/magellan}


   2. Footnote:
      It can be indicated with a footnote next to the paper title or next to the first sentence of the abstract. For example:
      > \title{Magellan: Navigating the Latent Space for Innovative Generation\thanks{Code is available at
  \url{https://github.com/your-repo/magellan}.}}

  Why not include the abstract?

   * Focus separation: The abstract should focus on "why (the problem)", "how (the method)", and "what are the results (contributions)". Code links belong to logistical information and would distract readers from the core academic content.
   * Length limitations: Top conferences have strict or unwritten word limits for abstracts, and every sentence should serve to demonstrate its academic value.
   * Conference process: During the anonymous review phase, any information that might reveal the author's identity (including public GitHub links) is not permitted. You will only add this link after your paper is accepted, when preparing the Camera-Ready version. At that time, placing it at the end of the introduction is the best choice.

  Summary:
  Please rest assured that there is absolutely no need to consider code links in the abstract right now. Just wait until your paper is accepted and then add the link at the end of the introduction.








