Papers with communication strategies
CAPC-CG: A Large-Scale, Expert-Directed LLM-Annotated Corpus of Adaptive Policy Communication in China (2026.acl-long)
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| Challenge: | Adaptive policy communication is a theory of governance in large, decentralized organizations where leaders exercise influence rather than precise control by combining clear and ambiguous instructions to calibrate discipline and flexibility. |
| Approach: | They propose an expert-directed annotation method that integrates codebook design, structured training, a two-step workflow, and LLM-based scaling. |
| Outcome: | The proposed method achieves a Fleiss’ kappa of 0.86 on directive labels, indicating high reliability. |
Human Alignment: How Much Do We Adapt to LLMs? (2025.acl-short)
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| Challenge: | Large Language Models (LLMs) are becoming a common part of our lives, yet few studies have examined how they influence our behavior. |
| Approach: | They propose a cooperative language game in which players aim to converge on a word and play a game in a group. |
| Outcome: | The proposed game shows that humans notice and adapt to differences regardless of whether they are aware they are interacting with an LLM. |
Collaborative Document Simplification Using Multi-Agent Systems (2025.coling-main)
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| Challenge: | Document simplification requires complex factors such as technical terminology, metaphors, and overall coherence. |
| Approach: | They propose a multi-agent framework for document simplification based on large language models that emulates the collaborative process of a human expert team through the roles played by multiple agents. |
| Outcome: | The proposed framework emulates the collaborative process of a human expert team through the roles played by multiple agents, addressing the intricate demands of document simplification. |
Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights (2022.tacl-1)
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| Challenge: | a robust dialogue agent cannot assume a cooperative conversational counterpart when deployed in the wild. |
| Approach: | They propose a theoretical model for identifying non-cooperative interlocutors . they use reinforcement learning to implement multiple communication strategies . |
| Outcome: | The proposed model is validated by using reinforcement learning to implement multiple communication strategies. |
When Allies Turn Foes: Exploring Group Characteristics of LLM-Based Multi-Agent Collaborative Systems Under Adversarial Attacks (2025.findings-emnlp)
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| Challenge: | a new study examines the group characteristics of adversarial agents in multi-agent collaborative systems . collaborative agents are tasked with generating counterfactual answers to a given collaborative problem . |
| Approach: | They evaluate collaborative systems under adversarial attacks and propose methods to mitigate them . they also introduce a new metric to quantify the robustness of collaborative systems against such attacks . |
| Outcome: | The proposed method has been proven effective against adversarial attacks. |
Post-Hoc Watermarking for Robust Detection in Text Generated by Large Language Models (2025.coling-main)
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| Challenge: | Existing methods for document simplification address complex factors such as technical terminology, metaphors, and overall coherence. |
| Approach: | They propose a multi-agent framework AgentSimp for document simplification based on large language models that simulates collaboration among agents through roles played by multiple agents. |
| Outcome: | The proposed framework produces simplified documents that are more thoroughly simplified and more coherent across various articles and styles. |
Simulating Crisis Cognition: A Computational Framework for Hypothesis Generation in Crisis Communication (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) have demonstrated remarkable fidelity in simulating social dynamics, yet using them to inform high-stakes crisis policy requires rigorous causal evaluation. |
| Approach: | They propose a framework that functions as an in-silico hypothesis generator to evaluate communication strategies by coupling real-world telemetry with 1,813 agents. |
| Outcome: | The proposed framework provides a rigorous testbed for evaluating strategies before human-subject trials. |