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pith:IKVP6CRT

pith:2026:IKVP6CRT7M5VK6DHTYNE7AESEY
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Auditing Stealth Sycophancy in Mental-Health Dialogue: Structured Clinical-State Diagnostics and Clean Matched Benchmarks

Beining Xu, Hanbo Zhang, Tianze Han, Yongming Lu

Dynamic Emotional Signature Graphs evaluate mental-health dialogue quality by modeling decoupled clinical states with asymmetric geometry, reaching 0.9353 macro-F1 on held-out data.

arxiv:2605.03472 v2 · 2026-05-05 · cs.CL · cs.AI

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Claims

C1strongest claim

On the 600-window held-out test aggregate, DESG-Ensemble achieves 0.9353 macro-F1, exceeding ConcatANN by 1.51 percentage points, BERTScore by 19.63 points, and TRACT by 33.81 points; feature ablations indicate that the clinical state manifold is the main discriminative substrate while graph-based trajectory components provide asymmetric scoring and interpretable diagnostics.

C2weakest assumption

That the labels in the constructed diagnostic stress-test benchmark accurately and independently reflect therapeutic quality via clinical direction, and that the decoupled clinical states and asymmetric geometry can be defined without circular dependence on those same labels or post-hoc tuning that inflates performance on the custom data.

C3one line summary

DESG uses dynamic graphs of decoupled clinical states and asymmetric geometry to evaluate therapeutic dialogue quality, reaching 0.9353 macro-F1 on a 600-window held-out test set and outperforming LLM judges and text metrics by large margins.

Receipt and verification
First computed 2026-05-26T02:04:11.917389Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

42aaff0a33fb3b5578679e1a4f8092262f9284be3b3ba46d9730b8b95474c845

Aliases

arxiv: 2605.03472 · arxiv_version: 2605.03472v2 · doi: 10.48550/arxiv.2605.03472 · pith_short_12: IKVP6CRT7M5V · pith_short_16: IKVP6CRT7M5VK6DH · pith_short_8: IKVP6CRT
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IKVP6CRT7M5VK6DHTYNE7AESEY \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 42aaff0a33fb3b5578679e1a4f8092262f9284be3b3ba46d9730b8b95474c845
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "0e04807f5ee5c8a5d605195c003b34a0d9cfd2e3dadd8591e6bdfa65bd55f0ac",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/publicdomain/zero/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-05T07:56:20Z",
    "title_canon_sha256": "2535aaaa4f4922ec5ec645adba918feb86743f5a6ad7a517bce384f56829699b"
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  "source": {
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    "kind": "arxiv",
    "version": 2
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}