Recall — A Typed-Edge Memory Substrate for AI Agents
Copyright 2026 Yash Aggarwal

This product includes software developed by the Recall project authors and
contributors.

Licensed under the Apache License, Version 2.0 (the "License"); you may
not use this software except in compliance with the License. You may obtain
a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations
under the License.

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Recall composes published mathematics from third-party research. The
following authors and works are gratefully acknowledged. None of these
authors or institutions endorse Recall or are responsible for its content
or correctness; the integration is the work of the Recall maintainers.

  - Søren Hauberg (DTU Compute) and collaborators
    "Pulling Back Information Geometry" (AISTATS 2022; arXiv:2106.05367)
    "Identifying Metric Structures of Deep Latent Variable Models"
    (ICML 2025; arXiv:2502.13757)
    "Spacetime Geometry of Denoising in Diffusion Models"
    (ICLR 2026 oral; arXiv:2505.17517)

  - Christian Igel (University of Copenhagen) and collaborators
    "Second Order PAC-Bayesian Bounds for the Weighted Majority Vote"
    (NeurIPS 2020; arXiv:2007.13532)
    "Chebyshev–Cantelli PAC-Bayes-Bennett Inequality"
    (NeurIPS 2021; arXiv:2106.13624)

  - Raghavendra Selvan (University of Copenhagen) and collaborators
    "BMRS: Bayesian Model Reduction for Structured Pruning"
    (NeurIPS 2024 spotlight; arXiv:2406.01345)

  - Mohammad Hajiaghayi (UMD) and collaborators
    "Prize-Collecting Steiner Forest 2-Approximation" (JACM 2025;
    arXiv:2309.05172)

  - Yann Ollivier (Meta FAIR)
    "Ricci curvature of metric spaces in random walks" (2009)

  - Aapo Hyvärinen (Helsinki) and collaborators
    Identifiability of dual encoders via auxiliary variables
    (AISTATS 2019; arXiv:1805.08651)

  - Hansen and Ghrist
    "Toward a spectral theory of cellular sheaves" (2019)

  - Wei et al.
    "Learning Sheaf Laplacian Optimizing Restriction Maps" (arXiv:2501.19207)

  - OSU NLP Group
    "HippoRAG / HippoRAG 2" — Personalized PageRank for memory

  - Kang et al.
    "C-RAG: Certified Generation Risks for RAG" (ICML 2024;
    arXiv:2402.03181)

  - Zhang et al.
    "RAG as Noisy In-Context Learning: A Unified Theory and Risk Bounds"
    (arXiv:2506.03100)

The 2024-2026 AI memory ecosystem (Mem0, Letta/MemGPT, Graphiti, Cognee,
HippoRAG, MemoryOS, EM-LLM, A-MEM, Hindsight, Supermemory, Mastra)
informed the design through their public artifacts and audited failure
modes.

This NOTICE file is provided as required by the Apache License 2.0
section 4(d). It must be retained in any redistribution.
