Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-09T23:48:36.019590Z
Paper Citation Record
Slot Machines: How LLMs Keep Track of Multiple Entities
Citation observations with source coverage and deterministic predicates. 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 2026-07-11T06:31:22.384518+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Counted states
18 of 18 outbound references displayed
- verified exact11
- verified fuzzy5
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f5288b2e-0484-4307-aa07-07342f645c7a
Slot Machines: How LLMs Keep Track of Multiple Entities Understanding intermediate layers using linear classifier probes
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:01:04.059381Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 466d200c-636a-4154-8f06-58bbb44007e6
Slot Machines: How LLMs Keep Track of Multiple Entities Burke, Tristan Hume, Shan Carter, Tom Henighan, and Christopher Olah
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T12:25:39.894710Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 43171d1e-7c69-4c3f-b85e-79efb3d43d4b
Slot Machines: How LLMs Keep Track of Multiple Entities Sparse Autoencoders Find Highly Interpretable Features in Language Models
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T14:01:04.072173Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation a058615d-a715-4440-950a-88349cd92929
Slot Machines: How LLMs Keep Track of Multiple Entities Representational Analysis of Binding in Language Models
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:01:03.962542Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation dd3de2ae-4022-44e0-8c28-6a86074cc888
Slot Machines: How LLMs Keep Track of Multiple Entities Measuring the persuasiveness of language models.https://www.anthropic.com/research/ measuring-model-persuasiveness
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T12:25:39.898190Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 92c1948e-7da8-463f-813c-6c4e664f19ac
Slot Machines: How LLMs Keep Track of Multiple Entities How do Language Models Bind Entities in Context?
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:01:04.033376Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation e75ba7d8-cbb3-4acf-a5a1-0c79dcb76b16
Slot Machines: How LLMs Keep Track of Multiple Entities Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-29T02:04:57.235642Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation d06bf59d-2d11-4382-ac51-f55497cd0304
Slot Machines: How LLMs Keep Track of Multiple Entities Representational similarity analysis – connecting the branches of systems neuroscience.Frontiers in Systems Neuroscience, 2:4
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T12:25:39.901605Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 2dd6379c-38d9-41c1-9176-663da8aaf276
Slot Machines: How LLMs Keep Track of Multiple Entities Locating and Editing Factual Associations in GPT
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T09:58:57.694057Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 6747b243-3128-4945-afb4-8b0ddce9227e
Slot Machines: How LLMs Keep Track of Multiple Entities In-context Learning and Induction Heads
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T14:01:04.006350Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation cdd2fa72-0248-4394-a7df-180d8b9c69ab
Slot Machines: How LLMs Keep Track of Multiple Entities AI Deception: A Survey of Examples, Risks, and Potential Solutions
Reference 11
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T14:01:04.046214Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 50ef22f3-fff3-4990-aa32-7d87f41117fe
Slot Machines: How LLMs Keep Track of Multiple Entities Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:01:04.079136Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 546b1e0a-dfe7-4c00-b66f-924928d37f89
Slot Machines: How LLMs Keep Track of Multiple Entities Steering Llama 2 via Contrastive Activation Addition
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T20:37:21.847050Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation a82001df-96a8-489f-8d12-01f8207c9fbb
Slot Machines: How LLMs Keep Track of Multiple Entities Towards Understanding Sycophancy in Language Models
Reference 14
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T14:01:04.052487Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation cc88c2e0-6b7f-44ba-9353-769e3c9c8af2
Slot Machines: How LLMs Keep Track of Multiple Entities Tensor product variable binding and the representation of symbolic structures in connectionist systems.Artificial Intelligence, 46(1–2):159–216
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T12:25:39.887782Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation ccfc4aaf-fa7a-40bd-ad39-8d7a84df5d7b
Slot Machines: How LLMs Keep Track of Multiple Entities Treisman and Garry Gelade
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T12:25:39.891027Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation c5707b0e-d2eb-4ebf-bbb0-6962fda2427d
Slot Machines: How LLMs Keep Track of Multiple Entities Steering Language Models With Activation Engineering
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T14:01:04.023514Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Observation 84589b15-46d6-4cab-b686-5432bf43894a
Slot Machines: How LLMs Keep Track of Multiple Entities Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T14:01:04.014750Z
Standing notice
No event found in the named queried sources as of 2026-07-11T06:31:22.384518+00:00.
Pith citing papers
No inbound Pith citation observations are available.