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Can language models faithfully translate between natural language and formal logic?
A broader line of inquiry — a family of 61 specific questions the research asks around this. Follow one into its inquiring-line page, or move sideways to a related line below.
Questions in this line of inquiry 61
Specific inquiring lines the field asks around this — ordered from the most general framing down to the most specific angle.
- Can LLMs translate between natural language and formal logic faithfully?
- Why do LLMs fail at semantic generalization despite grammatical accuracy?
- Why do LLMs struggle to translate natural language into logical formalizations?
- Can language models translate theorems faithfully without semantic loss?
- Why do LLMs fail at faithful autoformalisation of reasoning problems?
- Do LLMs struggle more with semantic accuracy than syntactic correctness across domains?
- Can language models perform genuine symbolic reasoning without semantic grounding?
- Why do language models fail at implicit discourse relations while handling explicit connectives?
- Why do LLMs perform better on explicit discourse connectives than implicit relations?
- Can LLM semantic representations exist without causally influencing their generation output?
- Why do LLMs understand efficient language but fail to produce it?
- What semantic information is necessary to preserve for sound LLM reasoning?
- Can explicit connectives compensate for missing intentional tracking in LLMs?
- Can language models perform purely symbolic reasoning when semantics are removed?
- Why do explicit discourse connectives help LLMs but implicit relations cause failures?
- Why do language models fail when semantic content is stripped away?
- How does implicit meaning processing limit LLM pragmatic reasoning?
- Why do LLMs fail at implicit elements in literary and poetic text?
- Can language models learn internal world models without explicit environment specifications?
- Why do LLMs generate logical forms without preserving semantic content?
- How do fixed pragmatic templates prevent models from understanding context?
- How do LLMs lose information when translating natural language to formal logic?
- Can the same LLM translation pattern work for other mismatches between user expression and system vocabulary?
- How does structural depth in sentences predict LLM annotation accuracy?
- Is paraphrase invariance a reliable assumption when deploying language models in production?
- Can LLMs improve at metaphor if they handle decoupled semantics better?
- Can language models keep secrets and control information strategically?
- What makes domain-specific utterance resolution harder for general large models?
- Why do explicit discourse connectives work when implicit relations fail?
- What makes human language fundamentally different from what language models produce?
- Why do LLMs produce semantically acceptable but pragmatically disengaged responses?
- Can LLMs decode their own hidden activations into natural language?
- Why do language models fail at understanding ambiguous or complex requirements?
- Can LLMs infer implicit meaning without surface linguistic markers?
- Can autoformalisation from natural language preserve semantic accuracy?
- Why do LLMs achieve only 24 percent accuracy on implicit discourse relations?
- Can we use LLM language without adopting LLM assumptions?
- How does the symbol grounding problem apply to artificial language systems?
- What specific linguistic features cause LLMs to fail at trivial entailment?
- Why do true and false LLM outputs use the same mechanism?
- How does the distance between natural language and formal notation affect translation accuracy?
- How does context collapse affect what language models can meaningfully communicate?
- How do different LLMs converge on similar argumentative structures independently?
- How do LLMs translate informal prose into logically correct formal specifications?
- How do dependency errors propagate through incorrectly formalized definitions?
- What distinguishes entity errors from relation errors in LLM output?
- What other structural limits exist at the language-formal boundary?
- How do rare linguistic registers differ from conceptually complex examples?
- How much semantic meaning survives when LLMs paraphrase poetry and literary text?
- Why does cross-text analogical reasoning fail when semantics decouple from symbols?
- Why do different LLMs converge on nearly identical outputs?
- What concrete problems do LLMs solve at the computational level?
- Why do LLM descriptions of argument schemes work better than formal definitions for classification?
- Can LLMs compute how presuppositions project through embedded clauses?
- How do LLMs compress literary language without losing essential nuance?
- How do politeness strategies depend on semantic ambiguity between literal and intended meaning?
- What is the difference between learning discourse patterns and learning abstract language?
- How does bidirectional entailment distinguish semantic equivalence from token similarity?
- Why do LLMs choose surface-order quantifier scope over contextually correct readings?
- Why do LLMs struggle with negation and exception handling?
- What makes colorless green ideas fail where Jabberwocky succeeds?