Browse State-of-the-Art › Multi-agent Integration
Multi-agent Integration
7 papers with code · 1 benchmark · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| BBAI Dataset (1 row) | MARS Encoder | One Agent To Rule Them All: Towards Multi-agent Conversational AI | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
7 shown of 7 papers with code (9 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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21 Jun 2024 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)Together with InfoNav, iAgents organizes human information in a mixed memory to provide agents with accurate and comprehensive information for exchange.
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Mitigating Bias in Queer Representation within Large Language Models: A Collaborative Agent Approach12 Nov 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedLarge Language Models (LLMs) often perpetuate biases in pronoun usage, leading to misrepresentation or exclusion of queer individuals.
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16 Oct 2024 1 repository listedWe propose a recursive learning approach that engages the model in multi-step reasoning, revisiting, and refining intermediate steps before producing a final output in training and inference phases.
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2 Mar 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverifiedIn this paper, we propose AutoDefense, a multi-agent defense framework that filters harmful responses from LLMs.
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21 Feb 2024 1 repository listedWith the rapid advancement of Large Language Models (LLMs), significant progress has been made in multi-agent applications.
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15 Mar 2022 1 repository listedTo address these problems, we introduce a new task BBAI: Black-Box Agent Integration, focusing on combining the capabilities of multiple black-box CAs at scale.
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31 May 2021 1 repository listedNowadays, IoT devices have an enlarging scope of activities spanning from sensing, computing to acting and even more, learning, reasoning and planning.
Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections