Hierarchical Frequency Tagging Probe (HFTP): A Unified Approach to
  Investigate Syntactic Structure Representations in Large Language Models and
  the Human Brain
Large Language Models (LLMs) demonstrate human-level or even superior
language abilities, effectively modeling syntactic structures, yet the specific
computational modules responsible remain unclear. A key question is whether LLM
behavioral capabilities stem from mechanisms akin to those in the human brain.
To address these questions, we introduce the Hierarchical Frequency Tagging
Probe (HFTP), a tool that utilizes frequency-domain analysis to identify
neuron-wise components of LLMs (e.g., individual Multilayer Perceptron (MLP)
neurons) and cortical regions (via intracranial recordings) encoding syntactic
structures. Our results show that models such as GPT-2, Gemma, Gemma 2, Llama
2, Llama 3.1, and GLM-4 process syntax in analogous layers, while the human
brain relies on distinct cortical regions for different syntactic levels.
Representational similarity analysis reveals a stronger alignment between LLM
representations and the left hemisphere of the brain (dominant in language
processing). Notably, upgraded models exhibit divergent trends: Gemma 2 shows
greater brain similarity than Gemma, while Llama 3.1 shows less alignment with
the brain compared to Llama 2. These findings offer new insights into the
interpretability of LLM behavioral improvements, raising questions about
whether these advancements are driven by human-like or non-human-like
mechanisms, and establish HFTP as a valuable tool bridging computational
linguistics and cognitive neuroscience. This project is available at
https://github.com/LilTiger/HFTP.
68f0c8c136f8b025381e1b23
Jingmin An
claimed_verified
2025-10-16T10:38:17.629Z
66a7267a474c222eb649bdbc
/avatars/83771cce0b91a5d88707d5fee3b3b88b.svg
Jingmin
user
GarfieldX
68f0c8c136f8b025381e1b24
Yilong Song
68f0c8c136f8b025381e1b25
Ruolin Yang
68f0c8c136f8b025381e1b26
Nai Ding
68f0c8c136f8b025381e1b27
Lingxi Lu
68f0c8c136f8b025381e1b28
Yuxuan Wang
68f0c8c136f8b025381e1b29
Wei Wang
68f0c8c136f8b025381e1b2a
Chu Zhuang
68f0c8c136f8b025381e1b2b
Qian Wang
68f0c8c136f8b025381e1b2c
Fang Fang
Hierarchical Frequency Tagging Probe (HFTP): A Unified Approach to
  Investigate Syntactic Structure Representations in Large Language Models and
  the Human Brain
Large Language Models (LLMs) demonstrate human-level or even superior
language abilities, effectively modeling syntactic structures, yet the specific
computational modules responsible remain unclear. A key question is whether LLM
behavioral capabilities stem from mechanisms akin to those in the human brain.
To address these questions, we introduce the Hierarchical Frequency Tagging
Probe (HFTP), a tool that utilizes frequency-domain analysis to identify
neuron-wise components of LLMs (e.g., individual Multilayer Perceptron (MLP)
neurons) and cortical regions (via intracranial recordings) encoding syntactic
structures. Our results show that models such as GPT-2, Gemma, Gemma 2, Llama
2, Llama 3.1, and GLM-4 process syntax in analogous layers, while the human
brain relies on distinct cortical regions for different syntactic levels.
Representational similarity analysis reveals a stronger alignment between LLM
representations and the left hemisphere of the brain (dominant in language
processing). Notably, upgraded models exhibit divergent trends: Gemma 2 shows
greater brain similarity than Gemma, while Llama 3.1 shows less alignment with
the brain compared to Llama 2. These findings offer new insights into the
interpretability of LLM behavioral improvements, raising questions about
whether these advancements are driven by human-like or non-human-like
mechanisms, and establish HFTP as a valuable tool bridging computational
linguistics and cognitive neuroscience. This project is available at
https://github.com/LilTiger/HFTP.
Hierarchical Frequency Tagging Probe (HFTP) identifies neuron-wise components in LLMs and cortical regions encoding syntactic structures, revealing differences in how LLMs and the human brain process syntax.
Hierarchical Frequency Tagging Probe HFTP frequency-domain analysis Multilayer Perceptron MLP representational similarity analysis left hemisphere language processing