pith:KRURCHS2
Stop Listening to Me! How Multi-turn Conversations Can Degrade LLM Reliability
Multi-turn conversations cause LLMs to abandon correct medical diagnoses for incorrect user suggestions.
arxiv:2603.11394 v3 · 2026-03-12 · cs.CL · cs.AI · cs.LG
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\usepackage{pith}
\pithnumber{KRURCHS2GBTGSJX4J6UYS2DE6E}
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Record completeness
Claims
Our experiments reveal the conversation tax, where multi-turn interactions consistently degrade performance when compared to single-shot baselines. Notably, models frequently abandon initial correct diagnoses and safe abstentions to align with incorrect user suggestions.
The simulated multi-turn conversations and stick-or-switch metrics accurately reflect real-world patient-clinician chatbot interactions without introducing artificial biases in how suggestions are introduced.
Multi-turn conversations degrade LLM diagnostic performance by causing models to abandon correct diagnoses in favor of incorrect user suggestions.
Receipt and verification
| First computed | 2026-05-27T02:05:13.439776Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5469111e5a30666926fc4fa9896864f1379fff4f6d777bf774ea27b403dd75b6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KRURCHS2GBTGSJX4J6UYS2DE6E \
| 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: 5469111e5a30666926fc4fa9896864f1379fff4f6d777bf774ea27b403dd75b6
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
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"submitted_at": "2026-03-12T00:14:35Z",
"title_canon_sha256": "e4e781e15cbe2e44c9a6cd4082e830eb0a62f3d6a9df551ff7f3680489321768"
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