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Paper Citation Record · LEDGER

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

As of 7 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 6 inbound Pith citation observations for arXiv:2605.11887.

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

pith.paper-citation-record.v1
2605.11887 v1

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-13T05:38:31.094834Z

measured 93 of 93 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:21:27.112037Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T13:59:52.526707Z

Reference resolution

87 of 87 outbound references displayed

  • verified exact13
  • verified fuzzy47
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch19

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe2efe93-d6a6-4621-9445-1d57bd2044e5 · outbound

This paper cites 2024 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , eprint=

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.155590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:794ac86abdfc4d40a8f49bca7a22518b0a7ebc04bdcf52a92009efacae91a5af

Observation 8e74f76b-8613-4737-829c-6dd0f0d75895 · outbound

This paper cites Connor Kissane, Robert Krzyzanowski, Arthur Conmy, and Neel Nanda.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Connor Kissane, Robert Krzyzanowski, Arthur Conmy, and Neel Nanda

Reference 2

Resolution
metadata mismatch
doi, observed 2026-05-13T05:42:20.788775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:0aa5209a2b34aed52540f17e715f0db82d98afafc5edf07995611a315802a0e3

Observation cd27844c-6a65-4a1e-8da5-55a0c36ed5cc · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.181046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:fb0f913eb0aa3a81c3304f3583bf8f78e3218d7367e1a8883c9a03bb671eb5c0

Observation 1dd2e3b3-8699-492e-aff2-3c9bd2bb2ce4 · outbound

This paper cites Hashimoto , title =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Hashimoto , title =

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.367768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:9e02cfd0c5f7915dbb837570e120e80828cec592f0639394b93a0bc412c812cc

Observation 9140eaaf-b41e-414a-b26b-2a94417dd3d3 · outbound

This paper cites Working Notes of CLEF 2024 - Conference and Labs of the Evaluation Forum , editor=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Working Notes of CLEF 2024 - Conference and Labs of the Evaluation Forum , editor=

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.349168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:833453239f66e4dbe89942fffa550354178d4d6c3a13f93e989137561600378d

Observation 933c3626-528d-4602-9959-0a0e9bc548fb · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.371875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:634b3ccca87c435d09494dcc03513bfbace85c7c7419ac0f25adbde2916a0d1e

Observation 6fb1e993-df14-447c-a288-2cba54a928a6 · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.344206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:e56c3da3a5d02151f370868367366ac0e1267a5710eccf108242ea9f03fe7335

Observation 8d887203-1bdf-4254-ae17-b9e889199d6b · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.328637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:69742a59be02bde1acf0309fa4276b5a682f497a8ac22d6d4033fdf773d9538a

Observation e82bd350-f81f-4ed2-a1bc-f3fed7033f9b · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.317822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:a0d65b0d21b0cd288e6a54da4208582d6dd39f09bfd430f24cc9d277a7363d60

Observation 07e8aaa3-7559-4211-bb79-f28d2a5b49c4 · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.324952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:8b6c80756dfeaf3c22a9bfe4ec3dc584939f4ab4bf4115f1f6b5bc8d2498746e

Observation 5fb62a94-b887-415c-b9b3-a1470b3e0198 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 11

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.108676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:7e4c0a7c6eed12e2cbacb2d94d69579c313d0a879c5ed0b3e1c75e3ea23d3c34

Observation 07dabe6c-882e-4693-9055-e8218234a99a · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.321309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:621d56b0977263e976a1b943d17400a3d70059053c64a52d234c54691a601160

Observation d84be32a-f7eb-48bb-a03d-2db78951ba2f · outbound

This paper cites OpenAI GPT-5 System Card.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models OpenAI GPT-5 System Card

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.087424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:ac5094401612fdda463b6ffa2ddbdd2a8195c1a45648ab824293da7c7c8d7ac3

Observation 9ab8894d-55db-4397-af43-162087dc098b · outbound

This paper cites doi: 10.1038/s41586-025-09422-z.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models doi: 10.1038/s41586-025-09422-z

Reference 14

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.798258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:bad250fe824a333cf1a439b0b12246f1371049408e669bc080a729f48bd6b0dc

Observation 2b1fef07-b4e9-4a31-814d-b942f74f2262 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.335041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:a5071ebf46a8fc6ca54b922f6b984fa595e5dc367aad0b9298874a8aa5a6b839

Observation 651ef618-4530-4dcb-843a-15407cab865b · outbound

This paper cites Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) , pages=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) , pages=

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.387627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:6ff6a9e4aed659f156621b426b237fefff12406acf990594b0003450f2c75541

Observation 6582d113-df35-4a73-9ad5-71326e0d1ba5 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Instruction-Following Evaluation for Large Language Models

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.134639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:446b99040eb233791b59efdccda96bb83f7bac6b63f3543a64bedda44f422660

Observation c62053c7-cd85-4c43-bf29-37833a821b32 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Measuring Massive Multitask Language Understanding

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.124707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:6c0df295f336fb21ca6723b5adada45d63203d3daade6eec8274271d98f63797

Observation 9916d4de-48a1-494a-b581-c40ab083cebe · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.113749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:03ce088b19fd6928a6ac0c99a6306c4757467d53688747b2d67671b3fea7f9c5

Observation ecbe2ca7-ab16-4e0b-8820-1714509d8007 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Findings of the Association for Computational Linguistics: ACL 2023 , pages=

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.403479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:afd08e12d67e26ab8d8497d149a3ec4278a5e198f2a04413b161515ee9f11126

Observation b8443918-009d-4ddb-9752-9e2128bfe8a7 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 21

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.154882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:94cb1f32cb808c482079a16e51f635ae9f746890f184f2aacfa7740242e578d1

Observation a96521f9-d358-474f-a4be-75cc94330bdd · outbound

This paper cites INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:42:21.159978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:d63b4f074b1458620236dd1422687951c27f62cf957fddfdfcd4d4f62018dc4f

Observation cbe47ab1-89a8-4993-b99c-dc47d5abea68 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.298676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:8a7759764e40cc22a69a356353fcde6c3b2113473cac3c1cd751c9f15ec6b9a0

Observation 2c9327b4-ab02-4b04-a3d8-6a88acdc031f · outbound

This paper cites SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T00:47:04.366365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:70e9a33bef19186ba415c0962f10086b55ba5c0768a5f00df0dae1a57d9f9517

Observation 470f611f-4335-45c5-878a-61512292131a · outbound

This paper cites Proceedings of the 31st International Conference on Computational Linguistics , pages=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Proceedings of the 31st International Conference on Computational Linguistics , pages=

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.294069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:a214ec390914a22b86a77521cdae82dffb4d4c26832e1dbdbd6ce55d48f61b94

Observation b06c50fc-b9db-428f-b0a2-001179f76e1c · outbound

This paper cites NeurIPS , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models NeurIPS , year=

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.303005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:c04c559b07d44cc1e6d1c4505ec077e136cf5dd547928e819ba00175b1a7d0b3

Observation 8d4731c7-6c96-4a33-a325-17f14b653367 · outbound

This paper cites Program Synthesis with Large Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Program Synthesis with Large Language Models

Reference 27

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.097566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:b9269560aa83dedffb9fb4d09eb8c4186a6eabcc142512e7763e9bf0d80ffc62

Observation 87085479-ed92-458f-a761-47ea591fa8fe · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.306799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:56e70579555578762d9357e45d37e721b199fa3c264ae9b0d53eb747cebcbbb7

Observation 50fc2b7f-0488-45cc-80e8-12ff46c4ad8e · outbound

This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.313522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:af2f7639fd782b46e3cc507691c59912d4258c75514f494021d308cba6444a9c

Observation 42a75c68-7c4a-4167-b92b-4f44e83e53d5 · outbound

This paper cites KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:42:21.149880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:3e08f89a2429c74b1353b0cd3ca8e72d90100253b6bb6fd055e72e7a227b736e

Observation cbe6dc98-bd95-469e-b7ad-c184c00cd5d1 · outbound

This paper cites Advances in Neural Information Processing Systems , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Advances in Neural Information Processing Systems , year=

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.408035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:ff00e51b4a7126f627f34f6c75bd56a98db14962ccb98d29880e98cdbf20b943

Observation 009a34ee-19c8-428e-ab45-61b9368249a4 · outbound

This paper cites 2023 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2023 , eprint=

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.276725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:3b482b22d788ed6effbff5a19ea7936e68cbf7749556c46a5d1c121a43b98928

Observation c4bcdecf-a9da-4e84-904f-ca6844b9a382 · outbound

This paper cites Is Your Code Generated by Chat.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Is Your Code Generated by Chat

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.266612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:06f0b9066bba242ef2abd07983fee679bfe40bde6d8a3c80d540a0641a1f11f4

Observation e97c4057-2cd9-4da0-adba-535e3f67f53a · outbound

This paper cites First Conference on Language Modeling , year =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models First Conference on Language Modeling , year =

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.285852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:8399ac5de01dde87e1e29abb29adfc569ec350001f1e6398e2289cbe079d53f4

Observation f6d60447-ce09-4d77-ae35-042e591483f3 · outbound

This paper cites MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:42:21.082359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:d1d5f87c901013d84f9da7eeb0408d00e2bba368e5bc68c0c0f66dc7ad2f6f77

Observation 5f316acc-b4d1-45e0-bb06-056424e289a1 · outbound

This paper cites 2024 , url=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , url=

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.262350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:716b1375b28a8315b0170773447f00966f8a7a65a72956edb1f624d6c852860f

Observation bce8a20f-6002-4649-87af-cdcdbb0d664f · outbound

This paper cites an unresolved cited work.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-05-13T10:17:39.395032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:5f755b544cccae04f6fe0bec752f9015d4fcc63750789d12b9f75f1507ab868a

Observation e9116b03-2e91-49ba-9d56-3f521bc8ea77 · outbound

This paper cites Controllable LLM Reasoning via Sparse Autoencoder-Based Steering.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Controllable LLM Reasoning via Sparse Autoencoder-Based Steering

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-29T01:24:27.631850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:ad08481c7f7bc32fa19cea9c02bec6746a7310795e877271613d3c1263f351ad

Observation 38694c25-682e-415e-9a63-00e944ff03d3 · outbound

This paper cites Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders

Reference 39

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.813501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:28cbfcd70e0e5e6d950c166c8e4c9294d173b329b8741dc08ee3d084eaccad7b

Observation 4c8e9325-c0dd-4120-a83e-eb0df6a9aac0 · outbound

This paper cites 2026 , url=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2026 , url=

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.250272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:542533804089f56bdfe6fb62418786868246a8314acf8e5b88f3db2a9b5ac659

Observation 26b1a226-833d-4f08-b4dc-6a913e03fd2b · outbound

This paper cites The 2025 Conference on Empirical Methods in Natural Language Processing , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models The 2025 Conference on Empirical Methods in Natural Language Processing , year=

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.255049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:89a2af889df951b9d672e707d68432514c633b911e99826420b7ce478dae989a

Observation 516bd898-1a39-46b9-9ba3-f19b7a8898cc · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models The Fourteenth International Conference on Learning Representations , year=

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.241124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:98293cf81baa8c2e4f9c04c6ada6f90e8425636f76f52458e0c3f00eec5e340a

Observation d8cec90a-feff-4783-8e05-3f2fb9bade81 · outbound

This paper cites The 2025 Conference on Empirical Methods in Natural Language Processing , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models The 2025 Conference on Empirical Methods in Natural Language Processing , year=

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.399622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:35dc1c492d29221f38d8d5876ef4dd10c61da3a84bc1106491f9bd123383685d

Observation d4aee3d1-3a53-4040-85e5-4646248d2b9d · outbound

This paper cites SAEs Are Good for Steering – If You Select the Right Features , url=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models SAEs Are Good for Steering – If You Select the Right Features , url=

Reference 44

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.817425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:1fd311499254278bec9b11159b4f49d36901a817bb39b7bbc6e47211776cfea0

Observation 89e5c6e5-b444-4963-8c13-2b83433cf06e · outbound

This paper cites 2024 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , eprint=

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.245541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:dedf2d661afeadd06fd87b3386443ee3f219c81b9b6a1c290f7920c77f9b8504

Observation df4cf2bd-0804-4c85-b77c-4868c241fac0 · outbound

This paper cites 2026 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2026 , eprint=

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.233573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:12d7db8c198b783280f0008f4140f3a3b3a819ec138dc0423c4eb738d6174f59

Observation 1024e932-cf62-496f-8cef-80e50cdad591 · outbound

This paper cites Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-29T02:04:39.904310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:d26ade903d4ff6f59716501f68e0ed2458938676012e30fbba3299c1d29f3d25

Observation cf826d38-738a-4994-a93a-94a1a1854e22 · outbound

This paper cites 2021 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2021 , eprint=

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.160510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:a5d183c909a37ab09d8378272fefb3badf100a629df375c247791f0e0f39f4a4

Observation 57f522bd-e771-4154-aa10-88455e014414 · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Forty-second International Conference on Machine Learning , year=

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.166249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:19bee362067c3f19fa12ea32e0d6d21da30087fd676e5fe7bde36034f549f624

Observation 6f144e3e-a45a-427b-b8d9-9b3bd26e0b77 · outbound

This paper cites Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.092333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:0b282937250ed7547f303d52c56511eadff050e40d6dfa0828dd26a42158cd6e

Observation 189ca4c1-933a-45ee-9609-d7a2aa9a1280 · outbound

This paper cites Automatically Interpreting Millions of Features in Large Language Models , booktitle =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Automatically Interpreting Millions of Features in Large Language Models , booktitle =

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.230410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:7c8ca2ae6a59c2412efe2aa06bcd1c9089168910e92d514307a54cb65cc61c74

Observation 1f0b19c6-5671-4e66-aad2-cb60bcd2e105 · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition , url =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Steering Llama 2 via Contrastive Activation Addition , url =

Reference 52

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.806429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:27deb859531cd82a2b6eb29699d0147b80fa7ddf821d92922429836c892bd64f

Observation faa2a36e-cccb-4985-b630-8bb727c0e3b9 · outbound

This paper cites Steering Large Language Model Activations in Sparse Spaces.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Steering Large Language Model Activations in Sparse Spaces

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:42:21.056231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:68a9df32e9584f9f8ac74035a2676b6b29c7e97ea1f0da9db361f1a4107f6cb1

Observation 62856a53-7729-4fae-9cdc-7316c7d25c14 · outbound

This paper cites SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:42:21.061616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:30c684b5796910182dcc97822045c88813e1c4627dacc8644a8d6b5cfb0a2abe

Observation b02da71b-81a8-45ae-add3-306d381f208a · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 55

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.066023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:0be1900143da8383406e18b4e846ee74dfea8a5ee28883312293854eeb7bb826

Observation 7c53b14b-2049-4673-8f10-b727fa002257 · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction , booktitle =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Refusal in Language Models Is Mediated by a Single Direction , booktitle =

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.236610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:7ea4a584e6d155cc9c1ad1b0043ef3c42a5469b908809faf02e406c3699cf5d1

Observation f67a4cd8-4d0b-4122-94c4-0e8737e60b3f · outbound

This paper cites The Thirteenth International Conference on Learning Representations.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models The Thirteenth International Conference on Learning Representations

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.281770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:393dab0db26b7157713d8641190a12e3c5f72815c2bbe40c5a03273d6c72a810

Observation 6797b22e-6226-43ce-bffd-3f968af54bb0 · outbound

This paper cites 2024 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , eprint=

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.337893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:3bcde56dba82db0fd7cd85840c5769521dd8bfc71e3ad9aecc907c87ebafa770

Observation f8343135-049a-4777-9b7e-48454d5652ab · outbound

This paper cites Transcoders find interpretable LLM feature circuits , url =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Transcoders find interpretable LLM feature circuits , url =

Reference 59

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.809910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:e04459e29c4b2d4b7264b06d5670c85158ef5979b9e1e80f11755d8a73b2d3fa

Observation 122b95de-36f1-493d-8121-9d34d1c3328f · outbound

This paper cites On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLM s.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLM s

Reference 60

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.802142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:7636aeb0b37b8bfdcf4f1aa50c119461b52e47ec54a25eb1e88e3c094b6183b0

Observation 2d0d86c5-2e0b-4e9e-9eeb-bad660591809 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.202471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:0d687858b939d52d2a9145022ed1962c210f36ec4d679958281ac403680487aa

Observation 8f9ceea8-52f5-4def-8423-423fa108f4cc · outbound

This paper cites 2024 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , eprint=

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.208255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:73d550c201d73a6243c219bbeaffc378909a5e1e0fff6bf0fefd2a7c3ce2fba5

Observation 20a61b1d-76e3-4180-bebd-16a5a2a48517 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Open Problems in Mechanistic Interpretability

Reference 63

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T18:30:06.348607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:097ed5a52347cbb74b15ddcdf1fc4d412307df2c0fb32b2f44fa0ef2efd9463f

Observation e3b2dd15-d303-433b-8dc8-a13bc0e491bf · outbound

This paper cites Mechanistic Interpretability for.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Mechanistic Interpretability for

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.217168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:4af0703421104aec54076876f0912f6a07bf1d808efc322eae8abf4d33a5db83

Observation e4c6f8e2-1830-4bce-8370-45b1af778f03 · outbound

This paper cites 2015 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2015 , eprint=

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.170357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:47dd3bbed75a94340228d92217c56d29d88c0aa25607b4a917e490ce90342b43

Observation 4111f5ea-935f-4cbc-8b20-281f37635cfa · outbound

This paper cites 2024 , url =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , url =

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.185394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:de11b7d3ad7a6f4b3652d068c9974fc5a1dbd8f993ef4e626a48f930414a3d74

Observation 08e08b28-1d7a-4b37-9636-4a65ffe7c074 · outbound

This paper cites Toy Models of Superposition.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Toy Models of Superposition

Reference 67

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.075661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:ed5b385319cd7e45ca227e46585fdfd7ba0556c33b26eb0f9871911eac67b64f

Observation 41b61b2a-0e62-4f69-b1fe-bf8184d0596d · outbound

This paper cites Transactions on Machine Learning Research , issn=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Transactions on Machine Learning Research , issn=

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.190556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:aca9d4a667336f112fe9a2ae0b32e79dec35047d024d3bfbd0025acc009e875e

Observation 51294e3b-a6e8-4639-bcfb-cdd7aadb8799 · outbound

This paper cites Emergent linear representations in world models of self-supervised sequence models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Emergent linear representations in world models of self-supervised sequence models

Reference 69

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.825345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:d6ddd7c7ace740bb094af96f02f9c09937b90aa7b7ed2e37a1e686316abf10b2

Observation 6d700937-1658-4ab8-b2a9-a51dbc6190e2 · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 70

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T05:42:21.165103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:291db7d6988c971c96abee4cdb8c74a2f47757645e79b6eb8c14cec211f5a176

Observation 1488ddc3-6744-4085-b709-ae5847491e1e · outbound

This paper cites Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Reference 71

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T13:15:10.863432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:c21a7ae4ca89ccc71a73cd9ed71194442052c600b3704c63f23a8319415c8168

Observation b37cc7d2-c21e-4791-9ec9-32fad356ef52 · outbound

This paper cites 2022 , journal=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2022 , journal=

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.195056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:1e857f28d81ad5a2772fd8fdd56148c8f2c3c2f3d5f8ea93a1529d3f796e7de5

Observation fec154cd-5af2-46fe-ba13-a7415fc8cfaf · outbound

This paper cites 2023 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2023 , eprint=

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.150733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:d3930c354b11778a76f5d824132f872106dcd81497cf14fa3c33b71177977fb0

Observation 8f2c1696-3622-48bd-9a54-9010efbf125f · outbound

This paper cites 2023 , journal=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2023 , journal=

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.375961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:db5787cd13d52f9aef0773b85f35d325cfc985c7c0deedd8a7bf72a308867b5e

Observation 8a502201-64f7-4f5a-a6fd-49f9a7c1d1ec · outbound

This paper cites arXiv preprint arXiv:2602.11180 , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv preprint arXiv:2602.11180 , year=

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:42:21.103854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:25da0bd2725a0060087572fdc48beddbadcef8b7a7fd247868d0908bea7843d1

Observation c20ea71f-5076-48a5-af6c-a7279a7f694b · outbound

This paper cites A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models

Reference 76

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.821205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:64723507d3e48675047f5419be425499a0f6569d23941d3cbafee7f7fe621161

Observation 321c0465-42be-49fd-8ed0-e038c87c05cd · outbound

This paper cites Route Sparse Autoencoder to Interpret Large Language Models.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Route Sparse Autoencoder to Interpret Large Language Models

Reference 77

Resolution
verified exact
doi, observed 2026-05-13T05:42:20.792575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:c4264e50c77404237e85501c7df8da8b1639c1f9c8db2a2795e0de8c38f313fb

Observation 3aa3ed59-a964-4661-b76f-bd5e62a52483 · outbound

This paper cites 2026 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2026 , eprint=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.176593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:231f2d8fc7eff61570a82be5446b38f20a7709c7e7b4e94469710ac0a19455bc

Observation efab13fb-bf58-4605-a720-4556bd092886 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.225904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:cb4c7e437f0d121700feae548398a6034011186156f039dc51a4dc866867e49b

Observation 6e3354bd-de04-448b-bdc5-3e1fda6fbad3 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.391417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:81f75712bd19a23cc3e3a464752b43e447b73cf42d5292f6759b2f2b60efdafa

Observation 936e0b35-86c2-44fa-8057-12b9798595fe · outbound

This paper cites 2026 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2026 , eprint=

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.221601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:7d9efcf578cac6b29bd574d69c24ea06aee641704c8aca7a9a25c6dbfd175463

Observation a446127f-adfc-47f6-b853-d208e1553b06 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.289871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:39055789be7b0428f120b2c88f501205f553a520bb784f990f34812da91b04c0

Observation e8c06cb9-8c3f-4c1e-9964-bb85979d6f69 · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models The Fourteenth International Conference on Learning Representations , year=

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.383419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:fb67ba5c35d24a128781e73ced6412bf91540f7873398975d5f80f2f60e4f507

Observation 6c05ad61-4928-4935-9c57-c405c5567ba5 · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.379643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:07bdddea29f86dc6f943e6753eff32586aef64e1802f95b297fff74f04187b95

Observation ed745c8a-8a78-49cd-8f39-4059203d0a0c · outbound

This paper cites 2025 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2025 , eprint=

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.352891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:fc865439832d9ae3628d7d3beca7c70dad68c6881bf925c6c4b4d0901f437b13

Observation 4f726eb9-7f63-49b5-bff7-d32e5e2430c9 · outbound

This paper cites 2024 , eprint=.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models 2024 , eprint=

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.358000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:16f3f19003861d5e750c6d385f792e7d6739e78ac23e9ba04f66e3f28be9e677

Observation 51df4bdd-bf38-40f3-90f8-3dd6215228e4 · outbound

This paper cites Attention is All you Need , url =.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models Attention is All you Need , url =

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T10:17:39.363642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T05:38:31.094834Z digest=sha256:84cca085e3051bfddfe044a72e905f663ab56a09564ccee3ab4771afe4f66c2a

Pith citing papers

Observation 050c8c33-356e-44e3-9af5-900dd7b78a48 · inbound

Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects cites this paper.

Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-06-28T19:12:34.970757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T19:06:21.846156Z digest=sha256:6700b9202fbeb5953f48864c6349a5ae4c8321d959452294cfbcd399612ec431

Observation 759271eb-c7de-4299-a5b5-e9e5fc5f47c2 · inbound

ICA Lens: Interpreting Language Models Without Training Another Dictionary cites this paper.

ICA Lens: Interpreting Language Models Without Training Another Dictionary Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-03T09:17:49.083578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T10:21:58.878499Z digest=sha256:f9ee4d6642d1fe8a924441bf78749ea8515372130a036dfee1c8e2df9d9e341d

Observation 88791ba5-c0e2-4e19-b9fd-63c1e10e6878 · inbound

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction cites this paper.

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T10:48:02.896269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T09:48:49.786021Z digest=sha256:f6cf819a5f440b1371e95b60bb0647895382e45c341be1e11ab509868a21b0c3

Observation a187e3ea-eb0d-44ce-9626-e615e45206b9 · inbound

Discovering Millions of Interpretable Features with Sparse Autoencoders cites this paper.

Discovering Millions of Interpretable Features with Sparse Autoencoders Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-04T12:59:53.076232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T05:34:00.754172Z digest=sha256:4e119259c0d95dc79de8f15df8d61aeeb5f6e67e3682942b38a3968195fed3c8

Observation 34332875-7d04-476a-804f-c529fe35343f · inbound

Forecasting With LLMs: Improved Generalization Through Feature Steering cites this paper.

Forecasting With LLMs: Improved Generalization Through Feature Steering Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-07-04T13:59:52.528004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T04:42:01.073777Z digest=sha256:f7c13f4b80a4b65e4f1f8313d61b2c9630be412c393e31ae640c3e194f1a2690

Observation 6b8c3433-9075-43b9-84cc-c0f0a60d5cc9 · inbound

Task Competence Is Not Instruction Following: Evaluating Instruction-Conflicting Behavior in Small Language Models cites this paper.

Task Competence Is Not Instruction Following: Evaluating Instruction-Conflicting Behavior in Small Language Models Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-01T12:21:27.112037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:21:27.112037Z digest=sha256:1aebbcce5284913a5216694fa5cfeba57054b6a6d5b140b895f4569a6ea75a92