Pith. sign in

Paper Citation Record · LEDGER

SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2405.17890.

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

pith.paper-citation-record.v1
2405.17890 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:16:55.401740Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:59:36.447967Z

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 534e8948-2c21-4721-a58e-99ade183079e · inbound

Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents cites this paper.

Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 149

Resolution
verified exact
arxiv_id, observed 2026-05-12T13:36:57.199148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-12T13:36:57.011451Z digest=sha256:2ec13cc5243d00de7fbf57985457ca33075c195a6f40760c414d7e2a993bb765

Observation 7415d9d1-2109-4623-ab93-251efe366dc1 · inbound

A Survey on Sequential Recommendation cites this paper.

A Survey on Sequential Recommendation SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 161

Resolution
unresolved
no resolver link, observed 2026-08-11T13:47:37.859294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.859294Z digest=sha256:b7876924efb232b45472b275e2fca013ffb5aa9d9827ca91b99279206a2e5c95

Observation a5a068b5-2ecf-4367-b303-45f100bdab14 · inbound

Large Language Model Enhanced Recommender Systems: A Survey cites this paper.

Large Language Model Enhanced Recommender Systems: A Survey SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-11T13:11:48.804796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:11:48.804796Z digest=sha256:bd60de551c8e2f9314ec7f193e66aabe826eec670b04eb34bb845b9708920cc6

Observation 598d393b-b37e-47a5-a6cc-d94a09ac037e · inbound

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models cites this paper.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-04T22:32:17.811380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:32:17.811380Z digest=sha256:23eb9cdec0d16d249a0c9515ce3f1935ef6fe863f4826547ad96f848abc192ce

Observation e17eb3dd-9035-4ab3-a4fa-8bb090dd240c · inbound

Sensory-Aware Sequential Recommendation via Review-Distilled Representations cites this paper.

Sensory-Aware Sequential Recommendation via Review-Distilled Representations SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:40:11.657433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T17:38:39.607878Z digest=sha256:d71fd5ea28f2f684a5aea7fa908e813930c68b0f2498c612096dc7edfa9fac24

Observation 8b2a197d-5def-4226-bee7-33564836cdde · inbound

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning cites this paper.

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:20:10.457959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-10T11:17:43.769244Z digest=sha256:f2dfb42761e074597b0479c08a584765f4eee0b8466421e8d5d37eb3571513d1

Observation 21adb2fa-ae19-4a18-98a7-a2cac64849d5 · inbound

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation cites this paper.

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 129

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:31:22.138127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T17:30:44.919870Z digest=sha256:67ec02a45c95175d1d8dc6da662a893a1d88e5db9f2093b7bf629d3ce895d08a

Observation 99d34f89-89a2-455a-a6f5-048d61e9693c · inbound

Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation cites this paper.

Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T05:59:36.451418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-26T15:16:26.994672Z digest=sha256:919a936c2bc130540ecb691d0bec9f9b4204999690a83ac3a26a5e644501c7f3

Observation 33e640b5-cb3a-498e-a290-0c8c883d9727 · inbound

TSPORec: Token Selection via Preference Optimization for LLM-Based Sequential Recommendation cites this paper.

TSPORec: Token Selection via Preference Optimization for LLM-Based Sequential Recommendation SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-11T14:16:55.401740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:16:55.401740Z digest=sha256:dee3bb05f938d73b0f53758b8e15e8aa2f48eff5d34716ee6e5401dfb382e73c