Paper Citation Record · LEDGER

HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2410.02694.

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

pith.paper-citation-record.v1
2410.02694 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:07:33.792487Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1ea32d87-5046-413e-be99-b96caf472c65 · inbound

SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model cites this paper.

SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 246

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:30:03.062768Z

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 a61a6ba2-5a9d-4e63-bf3a-bf0dfeedc3fe · inbound

NoLiMa: Long-Context Evaluation Beyond Literal Matching cites this paper.

NoLiMa: Long-Context Evaluation Beyond Literal Matching HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T20:07:33.792487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87e77dc3-cefc-4599-b02b-e6c49b622e11 · inbound

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? cites this paper.

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:26.649185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e9d54c-f2ab-49f2-9bfe-d1246d76f661 · inbound

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models cites this paper.

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-07T14:08:14.241741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23303ff9-36c3-4125-bd84-9493b8df1701 · inbound

AbsenceBench: Language Models Can't Tell What's Missing cites this paper.

AbsenceBench: Language Models Can't Tell What's Missing HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T04:13:17.791605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d1600d-058a-45d6-979d-5805a244b512 · inbound

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework cites this paper.

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:12.557157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 573f45ed-7569-4f96-b52f-7dbd576adc02 · inbound

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions cites this paper.

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:20:22.281395Z

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 19a2db10-b3d0-44e6-af6f-cc712ef51006 · inbound

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions cites this paper.

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:36:05.767328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c53058d7-0c5f-4868-9881-57a94bea899b · inbound

Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models cites this paper.

Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:56.251833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6aead0e6-90b4-47e9-bc0a-19cb0e7972fa · inbound

GLM-5: from Vibe Coding to Agentic Engineering cites this paper.

GLM-5: from Vibe Coding to Agentic Engineering HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:46:41.099372Z

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 93de6723-5a0e-4978-929a-02d8b6751012 · inbound

PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments cites this paper.

PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-21T09:59:59.098721Z

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 03e463e2-514e-4f33-bdd5-59d59e23b9f2 · inbound

Internalized Reasoning for Long-Context Visual Document Understanding cites this paper.

Internalized Reasoning for Long-Context Visual Document Understanding HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:53:27.832387Z

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 d29ebaf7-1cab-43dd-942c-9a576f9e68f5 · inbound

Internalized Reasoning for Long-Context Visual Document Understanding cites this paper.

Internalized Reasoning for Long-Context Visual Document Understanding HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-13T15:50:49.083652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 521582f8-285d-4bce-9683-cfd98a865bfc · inbound

AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments cites this paper.

AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:30:49.439342Z

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 951da3d5-e3e3-4fcf-b748-87e9df62b2ce · inbound

PolicyLong: Towards On-Policy Context Extension cites this paper.

PolicyLong: Towards On-Policy Context Extension HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:55:59.860500Z

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 246c1295-99e0-4794-9171-795cdf0fb9b3 · inbound

Supplement Generation Training for Enhancing Agentic Task Performance cites this paper.

Supplement Generation Training for Enhancing Agentic Task Performance HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-10T00:59:49.544323Z

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 27048f3d-6cb3-415d-b813-fb1c731673e5 · inbound

CL-bench Life: Can Language Models Learn from Real-Life Context? cites this paper.

CL-bench Life: Can Language Models Learn from Real-Life Context? HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:41:27.021854Z

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 219323fa-36d1-44ef-9d51-6f219bd8e7c2 · inbound

XekRung Technical Report cites this paper.

XekRung Technical Report HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 200

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:51:14.793114Z

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 ae37a2ae-a224-469f-aaf0-22e966c4aea3 · inbound

Retrieval from Within: An Intrinsic Capability of Attention-Based Models cites this paper.

Retrieval from Within: An Intrinsic Capability of Attention-Based Models HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:41:10.509957Z

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 7af95d44-3ce3-4012-8499-0b6c340a8bb8 · inbound

Retrieval from Within: An Intrinsic Capability of Attention-Based Models cites this paper.

Retrieval from Within: An Intrinsic Capability of Attention-Based Models HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:50:55.410903Z

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 7edf4609-ca80-4b36-abc7-b6c951ff0710 · inbound

Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing cites this paper.

Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:51:29.079752Z

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 0fa1d0be-b2df-4c0c-8f3d-41ccb54a0b67 · inbound

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues cites this paper.

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T03:57:12.685628Z

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 e9354fae-bb7e-4e68-b278-fb5a13ac9c0d · inbound

MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models cites this paper.

MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:05:04.246831Z

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 db3126e0-991e-48b6-ba5c-4b502e76ab9f · inbound

MemTrace: Probing What Final Accuracy Misses in Long-Term Memory cites this paper.

MemTrace: Probing What Final Accuracy Misses in Long-Term Memory HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T03:20:26.597377Z

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 f952f4f6-6a0a-4837-b8db-c67ec05b0c78 · inbound

Uncertainty-gated selection for block-sparse attention cites this paper.

Uncertainty-gated selection for block-sparse attention HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T22:15:14.580916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347f2a62-616e-47f3-86fb-a6b862b274c0 · inbound

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE cites this paper.

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-07-10T20:07:33.460361Z

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 f78bcb0a-a59f-4e16-b56d-98590a653c64 · inbound

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE cites this paper.

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-13T06:47:09.927626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 155aab53-fb26-499f-9c33-34b65ef412e5 · inbound

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents cites this paper.

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 143

Resolution: verified exact; local_arxiv, observed 2026-07-10T01:36:44.141102Z

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 668b0072-bef2-4180-a91a-f3d24743d65a · inbound

WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning cites this paper.

WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-13T03:52:24.872919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b9d11d5-bfea-4a30-a41a-fdc19305862f · inbound

WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning cites this paper.

WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T07:40:58.349130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ed6ac1d-fda7-4d4a-9110-b6dbfa8945d8 · inbound

E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios cites this paper.

E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-30T15:06:50.760396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e976dbf-c023-4458-a613-38acc352a6f7 · inbound

HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following cites this paper.

HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T02:36:10.030487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45d857b8-dd7b-4310-abb1-374c8be88b12 · inbound

LongCat Sparse Attention: Taming the Lightning via Streaming-aware Hierarchical Cross-Layer Indexing cites this paper.

LongCat Sparse Attention: Taming the Lightning via Streaming-aware Hierarchical Cross-Layer Indexing HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:00.494998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.