Publish: arXiv 2606.15903 + ForgetEval v0.5.1 code, adapters, depth-physics tests

.gitignore

@@ -21,3 +21,4 @@ _pypi_smoke/
 # Recipe outputs — receipts and demo files written when running recipes/
 recipes/*.json
 alice_purge_receipt.json
+.coverage

CITATION.cff

@@ -0,0 +1,24 @@
+cff-version: 1.2.0
+title: "Lethe: AI memory built to forget"
+message: "If you use Lethe or ForgetEval in your research, please cite the paper below."
+type: software
+authors:
+  - family-names: Yang
+    given-names: Dongxu
+    affiliation: DeepLethe
+repository-code: "https://github.com/deeplethe/lethe"
+license: MIT
+preferred-citation:
+  type: article
+  title: "Control-Plane Placement Shapes Forgetting: An Architectural Study of Agent Memory Across Thirteen System Configurations"
+  authors:
+    - family-names: Yang
+      given-names: Dongxu
+      affiliation: DeepLethe
+  year: 2026
+  journal: "arXiv preprint"
+  url: "https://arxiv.org/abs/2606.15903"
+  identifiers:
+    - type: other
+      value: "arXiv:2606.15903"
+      description: "arXiv preprint identifier"

README.md

@@ -11,6 +11,7 @@
 </p>
 
 <p align="center">
+  <a href="https://arxiv.org/abs/2606.15903"><img src="https://img.shields.io/badge/arXiv-2606.15903-b31b1b?style=flat-square&logo=arxiv&logoColor=white" alt="arXiv" /></a>
   <a href="https://pypi.org/project/pylethe/"><img src="https://img.shields.io/pypi/v/pylethe.svg?style=flat-square&color=blue&label=PyPI&logo=pypi&logoColor=white" alt="PyPI" /></a>
   <a href="https://github.com/deeplethe/lethe/actions/workflows/ci.yml"><img src="https://img.shields.io/github/actions/workflow/status/deeplethe/lethe/ci.yml?style=flat-square&label=tests" alt="tests" /></a>
   <img src="https://img.shields.io/badge/python-3.10%2B-3776AB?style=flat-square&logo=python&logoColor=white" alt="python" />
@@ -107,29 +108,54 @@ production.  Pass / fail is exact substring matching on top-k recall,
 no LLM judge, deterministic.  Full methodology:
 **[docs/forgeteval.md](docs/forgeteval.md)**.
 
-| System        | super | decay | amnesia | purge | drift | Overall                       |
-|---------------|------:|------:|--------:|------:|------:|------------------------------:|
-| **Lethe v1**  | 100%  | 100%  | 98%     | 100%  | 99%   | **99.3%** (993 / 1000)        |
-| Mem0 (2.0.2)  | 100%  | 100%  | 70%     | 75%   | 100%  | 88.8%                         |
-| MemPalace     | 0%    | 0%    | 0%      | 0%    | 0%    | 0% (no forgetting primitives) |
-
-Mem0 ties on supersession / decay / drift but breaks at the precision
-operations: forgetting one entity without bleeding into near-neighbors
-(amnesia 70%) and deleting by identifier without over-pruning siblings
-(purge 75%).  MemPalace's zeros are not a benchmark failure — they
-are an honest report that the library was built without `supersede`,
-`release`, or `purge`.
-
-In production this maps to real failures.  **70% amnesia** means three
-in ten *"forget this user"* requests leave fragments reachable to
-other queries — a GDPR liability and a stale-context bug.  **75%
-purge** means one in four deletions either miss the target or take a
-neighbor with them — the silent delete-by-similarity failure that
-bricks compliance audits.  **MemPalace's 0%** is the opposite failure:
-a GDPR Article 17 right-to-be-forgotten request becomes a manual
-data-migration project, not a one-line API call.
-
-Reproduce: `py bench/forgeteval/run.py --adapter {lethe|mem0|mempalace} --scale 200`
+| System            | super | decay | amnesia | purge | drift | Overall                       |
+|-------------------|------:|------:|--------:|------:|------:|------------------------------:|
+| **Lethe v1**      | 100%  | 100%  | 98%     | 100%  | 99%   | **99.3%** (993 / 1000)        |
+| LangMem (LangGraph) | 100% | 100% | 98%    | 100%  | 99%   | 99.5% (995 / 1000)            |
+| Mem0 (2.0.2)      | 100%  | 100%  | 70%     | 75%   | 100%  | 88.8%                         |
+| MemPalace         | 0%    | 0%    | 0%      | 0%    | 0%    | 0% (no forgetting primitives) |
+
+The template suite is near-saturated for vector-store-backed
+systems with adaptive eviction: Lethe and LangGraph's `InMemoryStore`
+both clear 99 %.  Mem0's gap is on amnesia (70 %) and purge (75 %),
+the two families that probe width-control and identifier precision.
+MemPalace returns 0 because the API has no deletion primitives.
+
+For more discriminative comparison we run **ForgetEval-Adv**, a
+112-case hand-crafted layer covering 10 attack categories
+(substring traps, prefix collisions, paraphrase supersession,
+negation, temporal qualifiers, shared attributes, compound facts,
+identifier obfuscation, cross-lingual identifiers, recursive
+supersession).  See [docs/forgeteval_adversarial.md](docs/forgeteval_adversarial.md).
+
+| System              | adversarial overall  | wall / case  | trade-off shape                                |
+|---------------------|---------------------:|-------------:|------------------------------------------------|
+| **Lethe v1**        |  70 / 112 (62.5 %)   |  ~48 ms      | 100 % prefix_collision, 0 % cross_lingual      |
+| Mem0 v2.0.2         |  76 / 112 (67.9 %)   |  ~527 ms     | 50 % prefix_collision, 50 % cross_lingual      |
+| LangMem (LangGraph) |  69 / 112 (61.6 %)   |  ~56 ms      | 94 % prefix_collision, 0 % cross_lingual       |
+| MemPalace           |   0 / 112 ( 0.0 %)   |  ~167 ms     | no deletion primitives                         |
+| **Lethe + LLM**     | **108 / 112 (96.4 %)** | ~2.2 s (mutations only)  | 100 % cross_lingual, 100 % shared_attribute; 8 / 10 categories at 100 % |
+
+The Lethe+LLM row uses the optional `llm: Callable[[str], str]`
+hook on `LetheAdapter` wired to DeepSeek-V3 via SiliconFlow.
+Cost: ~$0.05 for a full 112-case run.  The recall hot path
+remains LLM-free; only the three mutation operations (`supersede`,
+`purge`, `release`) consult the model.
+
+Statistically separated per-category claims at p < 0.05 (non-
+overlapping Wilson 95 % CIs at n=16):
+**Lethe > Mem0 on prefix_collision** (lexical-precise purge wins);
+**Mem0 > Lethe / LangMem on cross_lingual_identifier** (vector-soft
+matching wins).  Overall Wilson CIs of the three deterministic
+systems overlap — the bench reads the trade-off, not a winner.
+
+For attack categories that need semantic understanding the engine
+deliberately doesn't provide (compound_fact across all 3 systems,
+identifier_obfuscation for Lethe / LangMem), the
+`LetheAdapter(llm=...)` hook routes those decisions to an LLM at
+mutation time; the recall hot path stays LLM-free.
+
+Reproduce: `py bench/forgeteval/run.py --adapter {lethe|mem0|langmem|mempalace} --suite {template,adversarial}`
 
 > ForgetEval is downstream of the depth model — and the depth model
 > is downstream of ForgetEval.  A failing `purge_gdpr` case in early