Summary of Planning Vs Reasoning: Ablations to Test Capabilities Of Lora Layers, by Neel Redkar
Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers
by Neel Redkar
First submitted to arxiv on: 19 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research investigates the effectiveness of Low-Rank Adaptation (LoRA) layers in increasing reasoning and planning abilities. The study introduces HashChain Reasoning, a new evaluation dataset designed to deterministically test reasoning capabilities. The authors explore LoRA’s capabilities and limitations, shedding light on its potential for efficient model fine-tuning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how LoRA layers can make models better at making decisions and planning ahead. It creates a special testing set called HashChain Reasoning that helps figure out if models are really getting smarter or just doing things differently. |
Keywords
» Artificial intelligence » Fine tuning » Lora » Low rank adaptation
