The Grammar of Transformers: A Systematic Review of Interpretability Research on Syntactic Knowledge in Language Models
cs.CL, cs.AI
Submitted: 2026-01-09
Updated: 2026-08-31
Terminology
Sources
- Interpreting token compositionality in LLMs: A robustness analysis
- Differential syntactic and semantic encoding in LLMs
- Does BERT agree? Evaluating knowledge of structure dependence through agreement relations
- Constituency Parsing using LLMs
- LLMs as a synthesis between symbolic and distributed approaches to language
- Language Model Behavior: A Comprehensive Survey
- When does word order matter and when doesn't it?
- How Syntax Specialization Emerges in Language Models
- Tree Transformers are an Ineffective Model of Syntactic Constituency
- Deep Clustering of Text Representations for Supervision-free Probing of Syntax
- Large Language Models as Neurolinguistic Subjects: Discrepancy between Performance and Competence
- Do Attention Heads in BERT Track Syntactic Dependencies?
- MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs
- Manipulating language models' training data to study syntactic constraint learning: the case of English passivization
- Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention
- Syntax Representation in Word Embeddings and Neural Networks -- A Survey
- ChatGPT is a Potential Zero-Shot Dependency Parser
- Linguistic Interpretability of Transformer-based Language Models: a systematic review
- Language Models as Models of Language
- minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering