@inproceedings{gong-etal-2026-opacity,
title = "Opacity Is Not Privacy: Information-Constrained Latent Communication for Multi-Agent {LLM} Systems",
author = "Gong, Yao and
Xiang, Long and
Liang, Di and
Liu, Peiyang and
Lin, Zekai and
Hong, Mengze and
Wu, Xianjie and
Peng, Minlong",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.2186/",
pages = "49695--49717",
ISBN = "979-8-89176-459-0",
abstract = "Latent communication provides an efficient alternative to text-based exchange in multi-agent LLM systems by transmitting continuous hidden representations instead of natural-language messages. However, opacity is not privacy: latent messages may still carry private prompts, agent memory, or task-irrelevant sensitive information recoverable by downstream agents or adversaries. We study this risk through \textit{communicated latent messages}, the edge-level representations that cross agent boundaries and define the privacy interface of latent multi-agent systems. We identify two coupled leakage mechanisms: \textit{instantaneous leakage} from individual messages and \textit{propagation leakage} accumulated across multi-round transcripts.\par We propose \textbf{Information-Constrained Latent Communication} (ICLC), a model-agnostic communication-layer framework that constrains latent information exposure without modifying backbone LLM parameters. ICLC combines a receiver-conditioned latent bottleneck, adversarial regularization over messages and transcripts, and topology-aware gates that suppress unnecessary communication edges. Across private-context question answering, collaborative reasoning, and tool-use planning, ICLC preserves the utility benefit of latent communication while reducing average leakage from 0.747 to 0.398 compared with raw latent communication. These results suggest that privacy in latent multi-agent systems should be treated as a dynamic information-flow problem over messages, edges, and interaction rounds."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gong-etal-2026-opacity">
<titleInfo>
<title>Opacity Is Not Privacy: Information-Constrained Latent Communication for Multi-Agent LLM Systems</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yao</namePart>
<namePart type="family">Gong</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Long</namePart>
<namePart type="family">Xiang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Di</namePart>
<namePart type="family">Liang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Peiyang</namePart>
<namePart type="family">Liu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zekai</namePart>
<namePart type="family">Lin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mengze</namePart>
<namePart type="family">Hong</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Xianjie</namePart>
<namePart type="family">Wu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Minlong</namePart>
<namePart type="family">Peng</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing</title>
</titleInfo>
<name type="personal">
<namePart type="given">Hung-Yi</namePart>
<namePart type="family">Lee</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sunipa</namePart>
<namePart type="family">Dev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jessy</namePart>
<namePart type="family">Li</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Desmond</namePart>
<namePart type="family">Elliott</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Budapest, Hungary</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-459-0</identifier>
</relatedItem>
<abstract>Latent communication provides an efficient alternative to text-based exchange in multi-agent LLM systems by transmitting continuous hidden representations instead of natural-language messages. However, opacity is not privacy: latent messages may still carry private prompts, agent memory, or task-irrelevant sensitive information recoverable by downstream agents or adversaries. We study this risk through communicated latent messages, the edge-level representations that cross agent boundaries and define the privacy interface of latent multi-agent systems. We identify two coupled leakage mechanisms: instantaneous leakage from individual messages and propagation leakage accumulated across multi-round transcripts.\par We propose Information-Constrained Latent Communication (ICLC), a model-agnostic communication-layer framework that constrains latent information exposure without modifying backbone LLM parameters. ICLC combines a receiver-conditioned latent bottleneck, adversarial regularization over messages and transcripts, and topology-aware gates that suppress unnecessary communication edges. Across private-context question answering, collaborative reasoning, and tool-use planning, ICLC preserves the utility benefit of latent communication while reducing average leakage from 0.747 to 0.398 compared with raw latent communication. These results suggest that privacy in latent multi-agent systems should be treated as a dynamic information-flow problem over messages, edges, and interaction rounds.</abstract>
<identifier type="citekey">gong-etal-2026-opacity</identifier>
<location>
<url>https://aclanthology.org/2026.emnlp-main.2186/</url>
</location>
<part>
<date>2026-10</date>
<extent unit="page">
<start>49695</start>
<end>49717</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Opacity Is Not Privacy: Information-Constrained Latent Communication for Multi-Agent LLM Systems
%A Gong, Yao
%A Xiang, Long
%A Liang, Di
%A Liu, Peiyang
%A Lin, Zekai
%A Hong, Mengze
%A Wu, Xianjie
%A Peng, Minlong
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F gong-etal-2026-opacity
%X Latent communication provides an efficient alternative to text-based exchange in multi-agent LLM systems by transmitting continuous hidden representations instead of natural-language messages. However, opacity is not privacy: latent messages may still carry private prompts, agent memory, or task-irrelevant sensitive information recoverable by downstream agents or adversaries. We study this risk through communicated latent messages, the edge-level representations that cross agent boundaries and define the privacy interface of latent multi-agent systems. We identify two coupled leakage mechanisms: instantaneous leakage from individual messages and propagation leakage accumulated across multi-round transcripts.\par We propose Information-Constrained Latent Communication (ICLC), a model-agnostic communication-layer framework that constrains latent information exposure without modifying backbone LLM parameters. ICLC combines a receiver-conditioned latent bottleneck, adversarial regularization over messages and transcripts, and topology-aware gates that suppress unnecessary communication edges. Across private-context question answering, collaborative reasoning, and tool-use planning, ICLC preserves the utility benefit of latent communication while reducing average leakage from 0.747 to 0.398 compared with raw latent communication. These results suggest that privacy in latent multi-agent systems should be treated as a dynamic information-flow problem over messages, edges, and interaction rounds.
%U https://aclanthology.org/2026.emnlp-main.2186/
%P 49695-49717
Markdown (Informal)
[Opacity Is Not Privacy: Information-Constrained Latent Communication for Multi-Agent LLM Systems](https://aclanthology.org/2026.emnlp-main.2186/) (Gong et al., EMNLP 2026)
ACL
- Yao Gong, Long Xiang, Di Liang, Peiyang Liu, Zekai Lin, Mengze Hong, Xianjie Wu, and Minlong Peng. 2026. Opacity Is Not Privacy: Information-Constrained Latent Communication for Multi-Agent LLM Systems. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, pages 49695–49717, Budapest, Hungary. Association for Computational Linguistics.