mlsanityData to 14 Oct 2026

Strategic Dialogue Assessment: The Crooked Path to Innocence

arXiv 2506.01195 ↗First posted 1 Jun 2025cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

Language is often used strategically, particularly in high-stakes, adversarial settings, yet most work on pragmatics and LLMs centers on cooperativity. This leaves a gap in the systematic understanding of strategic communication in adversarial settings. To address this, we introduce SDA (Strategic Dialogue Assessment), a framework grounded in Gricean and game-theoretic pragmatics to assess strategic use of language. It adapts the ME Game jury function to make it empirically estimable for analyzing dialogue. Our approach incorporates two key adaptations: a commitment-based taxonomy of discourse moves, which provides a finer-grained account of strategic effects, and the use of estimable proxies grounded in Gricean maxims to operationalize abstract constructs such as credibility. Together, these adaptations build on discourse theory by treating discourse as the strategic management of commitments, enabling systematic evaluation of how conversational moves advance or undermine discourse goals. We further derive three interpretable metrics-Benefit at Turn (BAT), Penalty at Turn (PAT), and Normalized Relative Benefit at Turn (NRBAT)-to quantify the perceived strategic effects of discourse moves. We also present CPD (the Crooked Path Dataset), an annotated dataset of real courtroom cross-examinations, to demonstrate the framework's effectiveness. Using these tools, we evaluate a range of LLMs and show that LLMs generally exhibit limited pragmatic understanding of strategic language. While model size shows an increase in performance on our metrics, reasoning ability does not help and largely hurts, introducing overcomplication and internal confusion.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). First posted on arXiv 1 Jun 2025.

Builds on

0 of 0 references.

No references here yet.

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Communication Enhances LLMs' Stability in Strategic Thinking
  2. 2026GameTalk: Training LLMs for Strategic Conversation
  3. 2026Cheap Talk Stabilizes Strategic Interaction in LLM Agents
  4. 2026LinguaGame: A Linguistically Grounded Game-Theoretic Paradigm for Multi-Agent Dialogue Generation
  5. 2026The Anatomy of Conversational Scams: A Topic-Based Red Teaming Analysis of Multi-Turn Interactions in LLMs
  6. 2026Beyond Inefficiency: Systemic Costs of Incivility in Multi-Agent Monte Carlo Simulations
  7. 2026Moral Hazard in Multi-Agent Language Models
  8. 2025Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making