Line of inquiry
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Can language models build genuine grounding through interaction?
A broader line of inquiry — a family of 32 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 32
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?
- Why do language models presume common ground instead of building it?
- Can language models develop genuine social grounding through human interaction?
- Does social grounding in language improve through iterative human integration?
- Can convention formation improve communicative grounding beyond word sharing?
- Why do language models presume common ground instead of establishing it?
- Can static word-sharing create genuine communicative grounding between humans and models?
- How do LLMs differ from humans in their grounding mechanisms?
- Can LLMs use implicit background knowledge the way humans do in ordinary conversation?
- Do LLMs build common ground or assume it already exists?
- Why do LLMs presume common ground instead of building it?
- How do language models treat injected information as shared common ground?
- How does Wittgenstein's language games explain social grounding in LLMs?
- What distinguishes static grounding that presumes understanding from dynamic grounding that builds it?
- What makes social grounding different from constitutive linguistic agency?
- How does semantic grounding differ between human minds and language models?
- Why do LLMs lack the communicative scaffold that humans learn?
- Can LLMs build shared understanding through dynamic grounding rather than presuming it?
- Can training LLMs to form ad-hoc conventions improve their pragmatic reasoning?
- Can LLMs predict social norms without deep integration into linguistic practices?
- Does social grounding differ fundamentally from causal grounding in LLM behavior?
- How do humans learn language through communication differently than LLM text prediction?
- Why do language models respond to human social influence patterns?
- Why do users experience LLMs as peers rather than statistical tools?
- Why do LLMs presume common ground instead of building it carefully?
- Do language models understand tacit workplace norms and unspoken social rules?
- Can language models learn to form ad-hoc conventions through training?
- Can language models ground clarifications without vision and kinesthetic modalities?
- Does community integration change LLM properties or only relational positioning?
- How does Stalnaker's common ground model apply to machine conversation?
- Does DPO training with coreference chains teach spontaneous convention formation?
- What distinguishes social grounding from the equivalent social effects LLM text already produces?