Line of inquiry
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Can language models develop genuine communicative grounding with humans?
A broader line of inquiry — a family of 34 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 34
Specific inquiring lines the field asks around this — ordered from the most general framing down to the most specific angle.
- Why do language models presume common ground rather than build it?
- Can language models develop genuine social grounding through human interaction?
- Can static word-sharing create genuine communicative grounding between humans and models?
- Why do language models presume common ground instead of building it?
- How do LLMs differ from humans in their grounding mechanisms?
- Does social grounding in language improve through iterative human integration?
- What distinguishes static grounding that presumes understanding from dynamic grounding that builds it?
- Can convention formation improve communicative grounding beyond word sharing?
- Can LLMs use implicit background knowledge the way humans do in ordinary conversation?
- How does Wittgenstein's language games explain social grounding in LLMs?
- Can LLMs build shared understanding through dynamic grounding rather than presuming it?
- Do LLMs build common ground or assume it already exists?
- How do language models treat injected information as shared common ground?
- Why do LLMs presume common ground instead of building it?
- How does semantic grounding differ between human minds and language models?
- Does social grounding differ fundamentally from causal grounding in LLM behavior?
- What makes social grounding different from constitutive linguistic agency?
- Can language models ground clarifications without vision and kinesthetic modalities?
- Can functional semantic grounding substitute for true causal grounding?
- Does functional grounding through discourse patterns count as genuine semantic meaning?
- Can language models develop world models that ground meaning in causal reality?
- Why do LLMs lack the communicative scaffold that humans learn?
- How do LLM-based agents develop shared abstractions through interaction?
- How does face-saving avoidance drive LLM grounding failures?
- Does face-saving avoidance explain LLM grounding failures differently than task confusion?
- How does shared reference and grounding affect assumption detection in dialogue?
- How do world models create indirect causal grounding without physical environment contact?
- Why do LLMs presume common ground instead of building it carefully?
- How does Stalnaker's common ground model apply to machine conversation?
- How does the symbol grounding problem apply to artificial language systems?
- What training signals would models need to learn reciprocal common-ground construction?
- What distinguishes social grounding from the equivalent social effects LLM text already produces?
- What role does dynamic grounding play in achieving real mutual understanding?
- What makes communication relational in ways belief is not?