Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.08382.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:28:28.845441Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T14:45:43.121164Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1ae03475-945f-4cb3-8347-562a1d143813 · inbound
Revisiting LLM Value Probing Strategies: Are They Robust and Expressive? cites this paper.
Revisiting LLM Value Probing Strategies: Are They Robust and Expressive? Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:28:28.845441Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 804d4f28-d333-42c6-9101-1f053eb2d790 · inbound
SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models cites this paper.
SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T14:45:43.124439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4c9bf3d2-2f83-48d7-a853-bebd9d58697e · inbound
Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety cites this paper.
Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-07-15T13:17:48.274611Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.