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Scaling Model Capacity for Enhanced Reasoning
2025/06/14·StepFun can make mistakes, check important info.
I want you to help me refine a part of the text, which is a part of my technical report for the paper: ``` \section{Conclusion and Future Directions} We present Open-Reasoner-Zero (ORZ), the first comprehensive open-source implementation of large-scale reasoning-oriented RL training.  Our experiments show that vanilla PPO with GAE ($\lambda=1$, $\gamma=1$) and simple rule-based rewards, without KL regularization, effectively scales reasoning capabilities in language models.  This minimalist approach achieves competitive results compared to DeepSeek-R1-Zero while using significantly fewer training iterations. Our work provides in-depth analysis on training dynamics, model behaviors, and advantage estimation.  These insights offer practical guidance on scaling RL for complex reasoning tasks, addressing common challenges in stability and convergence. By releasing our complete training resources—code, configurations, data, and model weights across various sizes—we aim to democratize access to reasoning-oriented RL and provide valuable insights for the community.  We firmly believe we are at an early stage of this new scaling trend, and we are excited to share our findings and experiences with the community. Recall a bitter lesson from the past: the only thing that matters in the long run is what scales up effectively with increased computation and data. This fundamental insight continues to guide our research direction. In the future, we plan to further explore the following directions for continuously scaling up reasoning-oriented RL in order to build comprehensive reasoning agents: \begin{itemize}     \item \textbf{Data Scaling:} We will investigate how to effectively scale up by increasing the quantity, quality and diversity of training data.      By open sourcing our own training dataset, we hope to encourage the research community to contribute and share more training data.      \item \textbf{Model Scaling:} We will explore how model scaling affects reasoning abilities. We will investigate how multimodal models can enable richer reasoning across different modalities, and how extended sequence lengths can allow more room for complex multi-step reasoning.     \item \textbf{Test Time Scaling:} We will explore how to scale up test time computation. We will investigate how multi-turn interactions can enhance contextual reasoning abilities, how value model can assess reasoning trajectories, and how multi-agent scenarios can lead to more sophisticated reasoning strategies.     \item \textbf{Scenario Scaling:} We will explore how to scale up the complexity of reasoning for general scenarios. Our focus will be on generalizing reasoning capabilities to increasingly diverse tasks spanning creative writing, scientific discovery, and social interaction domains. \end{itemize} ``` I want to refine this part first: ```     \item \textbf{Model Scaling:} We will explore how model scaling affects reasoning abilities. We will investigate how multimodal models can enable richer reasoning across different modalities, and how extended sequence lengths can allow more room for complex multi-step reasoning. ``` This is really bad and not fluent. I think the logic is like this: 1. larger model has stronger capability, thus may have stronger reasoning pattern 2. multi-modal and seq length logic can follow original text But the expression is not good. I want you to help me refine this part.
Reason
思考过程

Okay, let's see. The user wants to refine the Model Scaling part of their technical report. The original text is a bit clunky and not very fluent. The main points are: larger models have stronger reasoning capabilities, multimodal models allow richer reasoning across different modalities, and extended sequence lengths support complex multi-step reasoning.

First, I need to make the structure clearer. The original point 1 about larger models should be the first thing mentioned. Then the other two points (multimodal and sequence length) follow. The current phrasing starts with "how model scaling affects reasoning abilities" which is a bit vague. Maybe start by directly stating that scaling up model size enhances reasoning capabilities. Then explain the two specific aspects: multimodal integration and sequence length.

Also, the original text uses "investigate how multimodal models can enable..." but maybe rephrase that to make it more active. Like "exploring how multimodal architectures can enhance cross-modal reasoning" or something like that. Also, "extended sequence lengths" could be rephrased to "increasing maximum sequence lengths" to sound more technical.

Check for fluency. The original sentences are a bit choppy. Maybe combine some ideas. For example, after mentioning model scaling's effect, use "including" to list the two aspects. Or use a structure like "This includes exploring..." followed by two bullet points.

Wait, but in the report, each main bullet point (Data, Model, Test Time, Scenario) is under an itemize. So the Model Scaling part is already a sub-item. The user wants to refine the sentence under Model Scaling.

Original: "We will explore how model scaling affects reasoning abilities. We will investigate how multimodal models can enable richer reasoning across different modalities, and how extended sequence lengths can allow more room for complex multi-step reasoning."

Possible improvements: Start by stating that scaling model size enhances reasoning capabilities. Then, in the same sentence, mention the two factors (multimodal and sequence length). For example: "We will explore how scaling model size enhances reasoning capabilities, including investigations into multimodal architectures to enable cross-modal reasoning and extending sequence lengths to accommodate multi-step reasoning chains."

But maybe split into two sentences. Alternatively, structure it as a main point followed by two sub-points. But since it's a technical report, perhaps keeping it concise is better.

Another angle: The original uses "affects" which is passive. Maybe "enhances" is more active. Also, "richer reasoning across different modalities" could be "cross-modal reasoning capabilities" or "reasoning that integrates multiple modalities".

Also, "extended sequence lengths" might be better as "increased sequence length limits" or "extended context windows".

So, putting it all together: "We will explore how scaling model size enhances reasoning capabilities, including investigations into multimodal architectures to enable cross-modal reasoning and extending sequence limits to support complex, multi-step reasoning processes."

Alternatively, use a colon to introduce the two aspects: "We will explore how scaling model size enhances reasoning capabilities, focusing on: (1) leveraging multimodal architectures for cross-modal reasoning and (2) increasing sequence length limits to accommodate extended reasoning chains."

But in the original structure, they might not want numbered points. The user's original text uses "and" to connect the two parts. So maybe: "We will explore how scaling model size enhances reasoning capabilities, including investigations into multimodal architectures to enable cross-modal reasoning and extending context windows to support complex, multi-step reasoning processes."

Check for repetition. "Extended sequence lengths" becomes "extending context windows". "Complex multi-step reasoning" is covered in "complex reasoning processes".

Also, check technical terms. "Context window" is a common term in LLMs for sequence length. Using that might be more precise.

So the refined version could be:

"We will explore how scaling model size enhances reasoning capabilities, including investigations into multimodal architectures to enable cross-modal reasoning and extending context windows to support complex multi-step reasoning processes."

Alternatively, to make it even smoother: "We will examine how model scaling amplifies reasoning abilities by exploring multimodal architectures for cross-modal reasoning and extending context windows to facilitate intricate, multi-step reasoning."

Wait, "amplifies" might be better than "enhances". Also, "examining" vs "exploring" – maybe "investigating" is more formal.

Another version: "We will investigate how scaling up model size strengthens reasoning capabilities, particularly through multimodal integration and extended context windows that accommodate complex multi-step reasoning."

Hmm. Maybe split into two sentences: "We will explore how scaling model capacity strengthens reasoning abilities. This includes investigations into multimodal architectures for cross-modal reasoning and extending context windows to support extended reasoning chains."

Yes, that might be better. Breaking it into two sentences for clarity. The first sentence states the main idea of model scaling affecting reasoning, the next sentence specifies the two aspects.

Original structure was two sentences. The user's example had two sentences. So perhaps keeping that structure but making it more fluent.

Revised first sentence: "We will explore how scaling model capacity enhances reasoning capabilities."

Second sentence: "This will include investigations into how multimodal architectures can enable richer cross-modal reasoning and how extended context windows can provide greater capacity for complex multi-step reasoning."

Alternatively: "Specifically, we will investigate leveraging multimodal models to enhance cross-modal reasoning and extending sequence limits to support more intricate multi-step processes."

But need to ensure technical accuracy. Also, avoid redundancy.

Final version might be:

"We will explore how scaling model capacity enhances reasoning capabilities, including investigations into multimodal architectures for cross-modal reasoning and extended context windows to support complex multi-step processes."

Yes, this is concise and covers both points. Uses "including" to introduce the two specific areas. Uses "extended context windows" which is precise.

Here's a refined version of the Model Scaling section with improved flow and structure:

text

Key improvements:

  1. Structured as a main point with sub-items for clarity
  2. Emphasized both broad scaling effects and specific technical dimensions
  3. Added concrete terminology ("depth-scaled parameterization", "deductive/abductive reasoning")
  4. Maintained technical rigor while improving readability
  5. Highlighted multi-modality and sequence extension as distinct research axes
  6. Used active voice and precise engineering vocabulary

This version maintains the original intent while presenting the research directions in a more logical and engaging manner suitable for technical publications.

This is not so good. Just one-liner is fine.
Reason
思考过程

Okay, the user is asking me to refine their technical report section again because they thought the previous attempt wasn't good. Let me start by understanding why they're dissatisfied.

In their initial query, they provided a section on "Model Scaling" that they found unfluent and wanted improvement. My first response broke it down into a structured list with sub-items. But now they're saying it's "not so good" and prefer a one-liner. Maybe they felt the bullet points were too detailed or made the section longer than desired, especially since they mentioned a one-liner is acceptable.

I need to consider the context. The original text was part of a technical report's conclusion and future directions. The user likely wants this section to be concise yet informative, especially since it's a part of a paper. They might prefer a more compact version that still conveys the key points without adding sub-items, which could make the overall document more streamlined.

Looking at the original version, the main points were about model scaling affecting reasoning abilities through multimodal models and extended sequence lengths. The user's logic was that larger models have stronger capabilities, so scaling up should improve reasoning. My previous attempt introduced sub-items which might have been unnecessary, making it less concise.

The user's preference for a one-liner suggests they want to keep the bullet points at the same level as the others in the list (Data Scaling, Test Time Scaling, etc.), without nested lists. So, I need to condense the information into a single, clear sentence that captures both multimodal integration and sequence length extension.

Let me try rephrasing it to maintain the original two aspects (multimodal and sequence length) in a single sentence. Maybe using "investigate how" for both points connected by a conjunction. Also, using terms like "cross-modal reasoning" and "extended context windows" can add technical precision without making it too wordy.

Testing the revised sentence: "We will investigate how increasing model capacity strengthens reasoning through multimodal integration and extended context windows to support complex multi-step processes." This combines both ideas into one line, keeps technical terms, and maintains conciseness. It should fit well with the surrounding bullet points and align with the user's request for brevity.

Here's a concise 1-liner refinement:
We will investigate how increasing model capacity strengthens reasoning through multimodal integration and extended context windows to support complex multi-step processes.

This retains:

  1. Core focus on scaling model size (increasing model capacity)
  2. Two key dimensions: multimodal reasoning + longer sequences
  3. Clear value proposition (strengthen reasoning, complex multi-step)
  4. Technical precision while avoiding unnecessary complexity