Papers with shallow attention layers
Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis (2024.emnlp-main)
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| Challenge: | Existing studies have found that arithmetic ability is limited to a few attention heads . existing studies do not elaborate on the mechanisms of these heads or how they influence FFN layers. |
| Approach: | They propose a method that identifies an internal logic chain consisting of four stages from input to prediction. |
| Outcome: | The proposed method improves prediction probabilities by amplifying coefficient scores of FFN neurons related to predictions. |
Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning (2024.acl-long)
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| Challenge: | Large language models exhibit high-level commonsense reasoning abilities, especially with enhancement methods like Chain-of-Thought (CoT). |
| Approach: | They propose a chain-of-thought-like method to elicit models' potential abilities to generate rationales and answers that are based on attribution tracing and causal tracers to probe the internal working mechanism of the LLM. |
| Outcome: | The proposed method eliminates Toxic CoT problems and improves the model’s overall commonsense reasoning performance by 5.5%. |