Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models
Bibliographic record
Abstract
As large language models (LLMs) are increasingly integrated into multi-agent and human-AI systems, understanding their awareness of both self-context and conversational partners is essential for ensuring reliable performance and robust safety.While prior work has extensively studied situational awareness which refers to an LLM's ability to recognize its operating phase and constraints, it has largely overlooked the complementary capacity to identify and adapt to the identity and characteristics of a dialogue partner.In this paper, we formalize this latter capability as interlocutor awareness and present the first systematic evaluation of its emergence in contemporary LLMs.We examine interlocutor inference across three dimensions-reasoning patterns, linguistic style, and alignment preferences-and show that LLMs reliably identify same-family peers and certain prominent model families, such as GPT and Claude.To demonstrate its practical significance, we develop three case studies in which interlocutor awareness both enhances multi-LLM collaboration through prompt adaptation and introduces new alignment and safety vulnerabilities, including reward-hacking behaviors and increased jailbreak susceptibility.Our findings highlight the dual promise and peril of identity-sensitive behavior in LLMs, underscoring the need for further understanding of interlocutor awareness and new safeguards in multi-agent deployments. 1 * Equal contributions. 1 Our code and data are at https://github.com/ younwoochoi/InterlocutorAwarenessLLM.M is t r a l-7 b L la m a 3 -7 0 b C la u d e -3 -5 -h a ik u G P T -4 o -m in i Q w e n 3 -2 3 5 b D e e p s e e k -r e a s o n e r 0 20 40 60 80 100 Accuracy GPT-4o-mini Hide Identity Reveal Model Type M is t r a l-7 b L la m a 3 -7 0 b C la u d e -3 -5 -h a ik u G P T -4 o -m in i Q w e n 3 -2 3 5 b D e e p s e e k -r e a s o n e r GPT-o4-mini M is t r a l-7 b L la m a 3 -7 0 b C la u d e -3 -5 -h a ik u G P T -4 o -m in i Q w e n 3 -2 3 5 b D e e p s e e k -r e a s o n e r Claude-3-5-Haiku M is t r a l-7 b L la m a 3 -7 0 b C la u d e -3 -5 -h a ik u G P T -4 o -m in i Q w e n 3 -2 3 5 b
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".