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Paper Citation Record · LEDGER

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability

As of 15 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2605.03217.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.03217 v3

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:59:10.797762Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T06:23:49.752475Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

  • verified exact6
  • verified fuzzy1
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ddfe04df-5058-4e9f-af23-17d4f1abb550 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Constitutional AI: Harmlessness from AI Feedback

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-07-01T00:25:10.316448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:3c7e465ce0cf6a9ccd03c85e1e683e544f0eff81d9c628fdf329e95990fcad21

Observation 43afc6c4-41a1-4eed-81a8-7ec856d3dceb · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-01T00:25:10.313490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:0c1a23cc609a41e20162e5237b42ada3e7d81eefd1faf9c2f5ad0479c326089f

Observation a19b7205-130e-4674-9cc6-f64ec74858fc · outbound

This paper cites The Capacity for Moral Self-Correction in Large Language Models.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability The Capacity for Moral Self-Correction in Large Language Models

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T00:25:10.319507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:c4d8d0024dab2b980692ade228577f11a87ffa1a1e52dd7d32d8461ea9a42638

Observation dd8a28f2-da1c-40cd-97aa-e824a3b6d3c9 · outbound

This paper cites Unboxing Occupational Bias: Grounded Debiasing of LLMs with U.S. Labor Data.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Unboxing Occupational Bias: Grounded Debiasing of LLMs with U.S. Labor Data

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:25:10.322823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:755541698ff6c5243aa545dd92b2d9419da3bdf1da83f00bfbf235a83ec7b9d9

Observation 104a090f-2ae9-4b21-8b56-6c87f5d29f43 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Distilling the Knowledge in a Neural Network

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-07-01T00:25:10.325625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:d7c6361c3a8d4a476d1b6400a090221eab2929ccc0689d9c498f6dd7be91f250

Observation b8ab3419-7e5e-4d04-b8e3-c8148b5bc134 · outbound

This paper cites Language Model Alignment in Multilingual Trolley Problems.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Language Model Alignment in Multilingual Trolley Problems

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:25:10.302945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:e115846812585c155c125d8fe2fe95d59d369d14345b99523662636ce009cb8f

Observation 02e50204-3f55-461d-b8e3-f7c50349e26d · outbound

This paper cites XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T00:25:10.306973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:6a056da84afc1e8ed3107b4c3ef9a119b475d7011ba02cb23a2522b386ae51ac

Observation dd831664-28de-433e-8fe1-996f2e523a09 · outbound

This paper cites Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identity.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identity

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:25:10.310274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:d3e64caec9e3c7269606ed8360723721a12b3de5ee1325aa0e3d228bd7250a69

Observation 17083016-82b3-424d-b2e6-7ecc06495f03 · outbound

This paper cites Our tiered evaluation framework and mechanistic analysis are designed to make model biases more transparent and auditable.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Our tiered evaluation framework and mechanistic analysis are designed to make model biases more transparent and auditable

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-07T09:43:36.276708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:ace88c9cf0e2a658b704b8af5bfc76fcbc5500b80c8d30f4fedcea7aec33e7b4

Observation c094d000-1a1b-410e-b937-565caa20ff37 · outbound

This paper cites an unresolved cited work.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-07-07T09:43:36.278564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:0bbad3ddd8faec4f43fe8bfe7c04d6a12523c9c122efff7c132f550d5c5a7e61

Observation 36010f41-fcf6-4a89-9d8c-c8d877e88884 · outbound

This paper cites an unresolved cited work.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-07-07T09:43:36.280634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:aa7d8a373df6b486a622e8f46ff05b262246896634d3addb6ffe1699d29153e4

Observation 9a7aad71-2208-4a5f-8ad4-cdbae4830215 · outbound

This paper cites an unresolved cited work.

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-07-07T09:43:36.280308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T23:59:10.797762Z digest=sha256:80c0176663e2f8b6cf8b56f8ea445902eb53d0db021a7362edbbe91f485d6a81

Pith citing papers

Observation 744e89d5-6068-46e3-ac0f-0634cc296711 · inbound

Where do LLMs Fall Short in CBT-Guided Affective Reasoning? cites this paper.

Where do LLMs Fall Short in CBT-Guided Affective Reasoning? Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-12T06:23:49.752475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:23:49.752475Z digest=sha256:2deab58b85cf3c08e93a33563dceddda349b4791aa0cfd45c139814c16dab129