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Paper Citation Record · LEDGER

Big data approach to Kazhdan-Lusztig polynomials

As of 17 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2412.01283.

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

pith.paper-citation-record.v1
2412.01283 v3

Coverage vector

measured 66 of 66 reference resolution

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measured 66 of 66 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

66 of 66 outbound references displayed

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External citation measurements

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Outbound references

Observation 0905c988-0f83-4f4d-8bf5-f19be550de2c · outbound

This paper cites Andersen and W.X.

Big data approach to Kazhdan-Lusztig polynomials Andersen and W.X

Reference 1

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Observation 3fa4d4e1-69a2-4aa3-b5ca-f9566b2f5463 · outbound

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 2

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Observation f3d61987-6897-4f32-8ece-82e3b515df23 · outbound

This paper cites The Beauty of Roots.

Big data approach to Kazhdan-Lusztig polynomials The Beauty of Roots

Reference 3

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 4

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Observation 49bf63ae-4a66-4b2d-8e51-470979bb4d91 · outbound

This paper cites (Co)Minuscule Hecke categories.

Big data approach to Kazhdan-Lusztig polynomials (Co)Minuscule Hecke categories

Reference 5

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Observation eeeb21b2-6717-4ef5-9c71-bbd10ee88685 · outbound

This paper cites Lower bounds for Kazhdan-Lusztig polynomials from patterns.

Big data approach to Kazhdan-Lusztig polynomials Lower bounds for Kazhdan-Lusztig polynomials from patterns

Reference 6

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Observation 2de3ff17-ab35-4edb-a1cd-1cbc13485b4d · outbound

This paper cites Bj \"o rner and F.

Big data approach to Kazhdan-Lusztig polynomials Bj \"o rner and F

Reference 7

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Observation b1a7c537-430b-46c9-be16-7fe38788448f · outbound

This paper cites Towards combinatorial invariance for Kazhdan-Lusztig polynomials.

Big data approach to Kazhdan-Lusztig polynomials Towards combinatorial invariance for Kazhdan-Lusztig polynomials

Reference 8

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Observation 21665df7-c51c-43d4-a32f-4f2451173b96 · outbound

This paper cites From moment graphs to intersection cohomology.

Big data approach to Kazhdan-Lusztig polynomials From moment graphs to intersection cohomology

Reference 9

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Observation db2329f6-a538-48f8-892a-b289d8040bd8 · outbound

This paper cites Some open problems on Coxeter groups and unimodality.

Big data approach to Kazhdan-Lusztig polynomials Some open problems on Coxeter groups and unimodality

Reference 10

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Observation 58b7293f-19a6-499c-8aa6-6ca4739981a7 · outbound

This paper cites Blocks of cyclotomic Hecke algebras and Khovanov-Lauda algebras.

Big data approach to Kazhdan-Lusztig polynomials Blocks of cyclotomic Hecke algebras and Khovanov-Lauda algebras

Reference 11

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Observation 89354276-4372-423b-a037-e9471bb37bd3 · outbound

This paper cites Roots, Schottky semigroups, and a proof of Bandt's Conjecture.

Big data approach to Kazhdan-Lusztig polynomials Roots, Schottky semigroups, and a proof of Bandt's Conjecture

Reference 12

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Observation 1737a6f7-cca7-42a5-aa05-c9a41fa8f186 · outbound

This paper cites Positivity results for the Hecke algebras of non-crystallographic finite Coxeter groups.

Big data approach to Kazhdan-Lusztig polynomials Positivity results for the Hecke algebras of non-crystallographic finite Coxeter groups

Reference 13

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Observation cb60bbc7-2261-4676-9110-b69d07e2735f · outbound

This paper cites Cvitanovi \'c.

Big data approach to Kazhdan-Lusztig polynomials Cvitanovi \'c

Reference 14

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Observation 310a0ae6-2a6f-4769-92fe-962672eb5abe · outbound

This paper cites Davies, P.

Big data approach to Kazhdan-Lusztig polynomials Davies, P

Reference 15

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Observation 2ca2f14b-0003-4350-a7de-adf40f048e80 · outbound

This paper cites Ball mapper: a shape summary for topological data analysis.

Big data approach to Kazhdan-Lusztig polynomials Ball mapper: a shape summary for topological data analysis

Reference 16

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 17

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Big data approach to Kazhdan-Lusztig polynomials Mapper-type algorithms for complex data and relations

Reference 18

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Big data approach to Kazhdan-Lusztig polynomials Shuffle algebras, homology, and consecutive pattern avoidance

Reference 19

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Observation dda891f9-6058-4982-934c-5597e473df3c · outbound

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Big data approach to Kazhdan-Lusztig polynomials Etingof, S

Reference 20

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This paper cites Content systems and deformations of cyclotomic KLR algebras of type $A$ and $C$.

Big data approach to Kazhdan-Lusztig polynomials Content systems and deformations of cyclotomic KLR algebras of type $A$ and $C$

Reference 21

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Big data approach to Kazhdan-Lusztig polynomials Link invariants, the chromatic polynomial and the Potts model

Reference 22

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Big data approach to Kazhdan-Lusztig polynomials Filaseta

Reference 23

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This paper cites On the Monoidal Center of Deligne's Category Rep(S_t).

Big data approach to Kazhdan-Lusztig polynomials On the Monoidal Center of Deligne's Category Rep(S_t)

Reference 24

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This paper cites Kazhdan-Lusztig polynomials and canonical basis.

Big data approach to Kazhdan-Lusztig polynomials Kazhdan-Lusztig polynomials and canonical basis

Reference 25

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 26

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Observation c9a414d3-5184-4802-82b3-8039d407b875 · outbound

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 27

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Big data approach to Kazhdan-Lusztig polynomials On the Likelihood of Comparability in Bruhat Order

Reference 28

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Observation 7d6714f2-173b-433c-96c5-2c0a901805c4 · outbound

This paper cites Milnor numbers of projective hypersurfaces and the chromatic polynomial of graphs.

Big data approach to Kazhdan-Lusztig polynomials Milnor numbers of projective hypersurfaces and the chromatic polynomial of graphs

Reference 29

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Observation 3008c058-f92e-47d7-a315-83a96d9d7368 · outbound

This paper cites The $p$-Canonical Basis for Hecke Algebras.

Big data approach to Kazhdan-Lusztig polynomials The $p$-Canonical Basis for Hecke Algebras

Reference 30

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 31

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Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 32

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Big data approach to Kazhdan-Lusztig polynomials Kazhdan and G

Reference 33

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Big data approach to Kazhdan-Lusztig polynomials A diagrammatic approach to categorification of quantum groups I

Reference 34

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Observation 09592712-a0f8-47c7-aa93-c3a2bd393c48 · outbound

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Big data approach to Kazhdan-Lusztig polynomials Web bases for sl(3) are not dual canonical

Reference 35

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Observation 9e9f2af8-de88-4b11-a893-dcdec8bf7c59 · outbound

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Big data approach to Kazhdan-Lusztig polynomials Spiders for rank 2 Lie algebras

Reference 36

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Big data approach to Kazhdan-Lusztig polynomials A formula to evaluate type A webs and link polynomials

Reference 37

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Observation 6b873c06-349b-4ef4-9fc1-28f4f71d9ecb · outbound

This paper cites Lacabanne, D.

Big data approach to Kazhdan-Lusztig polynomials Lacabanne, D

Reference 38

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source=arxiv_source observed=2026-08-12T04:39:37.974450Z digest=sha256:a5aaed9b9d159a5291dafb3e1c0d5fd8be944b38efa7a41c7147e986614f2ba8

Observation bb6913d8-9c1d-44a6-9a39-24ac6e37fb62 · outbound

This paper cites Big Data Approaches to Knot Theory: Understanding the Structure of the Jones Polynomial.

Big data approach to Kazhdan-Lusztig polynomials Big Data Approaches to Knot Theory: Understanding the Structure of the Jones Polynomial

Reference 39

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source=arxiv_source observed=2026-08-12T04:39:37.978958Z digest=sha256:d2a944cf2eb12cbaf501f8b99a926160449c2321ca4bafe2e88f241888c2dc7d

Observation 619f650b-ab8d-49e5-9233-3f0ba4948fc9 · outbound

This paper cites Hecke algebras with unequal parameters.

Big data approach to Kazhdan-Lusztig polynomials Hecke algebras with unequal parameters

Reference 40

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source=arxiv_source observed=2026-08-12T04:39:37.983021Z digest=sha256:3395ca545297bacca38d86f71b36570fff2cfff1f0e71c3e09e8ffca52171bc2

Observation 9365a44a-df95-4a44-9b8e-3692fb81dc4d · outbound

This paper cites Simple transitive $2$-representations of Soergel bimodules for finite Coxeter types.

Big data approach to Kazhdan-Lusztig polynomials Simple transitive $2$-representations of Soergel bimodules for finite Coxeter types

Reference 41

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source=arxiv_source observed=2026-08-12T04:39:37.986360Z digest=sha256:b2fa716f817d072c9f0fc601b517950ee9fd2cdb0a4f99b7657e9609ccd22c76

Observation 4a08ab71-59ee-4699-9127-65a090ddcbc9 · outbound

This paper cites The sl_3 web algebra.

Big data approach to Kazhdan-Lusztig polynomials The sl_3 web algebra

Reference 42

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:37.990514Z digest=sha256:63c8fcf61bdcd3bb4cb95e2220bf6c8076043fee696b131672e5de796de7f54d

Observation 0f65da2f-55f6-46f7-9e0b-2ec76eb48acd · outbound

This paper cites Cellularity of KLR and weighted KLRW algebras via crystals.

Big data approach to Kazhdan-Lusztig polynomials Cellularity of KLR and weighted KLRW algebras via crystals

Reference 43

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source=arxiv_source observed=2026-08-12T04:39:37.993962Z digest=sha256:9d8e9a832296eefa645d82a8aac174d40c41d4c2000b037034a837c4cddc4299

Observation a709a63b-4a4b-4097-ae1d-d3b35c5a1ad5 · outbound

This paper cites Distribution of roots of random real generalized polynomials.

Big data approach to Kazhdan-Lusztig polynomials Distribution of roots of random real generalized polynomials

Reference 44

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local_arxiv, observed 2026-08-12T04:39:38.417632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:37.997978Z digest=sha256:3fd6e6fabab2bc0e8cd8a3353ef2e1ddbe1a41d01654fa96ab3851c68d8327ca

Observation 2cee6d5c-468e-4751-8244-5efd27367d55 · outbound

This paper cites Categories generated by a trivalent vertex.

Big data approach to Kazhdan-Lusztig polynomials Categories generated by a trivalent vertex

Reference 45

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source=arxiv_source observed=2026-08-12T04:39:38.001639Z digest=sha256:aa53266b60f452cb83c98444a9c5dd4a8d39707488f20e46436d81092aa2a91b

Observation 8a909277-965e-4b4a-af3d-b4e47c944574 · outbound

This paper cites The O n- L ine E ncyclopedia of I nteger S equences, 2023.

Big data approach to Kazhdan-Lusztig polynomials The O n- L ine E ncyclopedia of I nteger S equences, 2023

Reference 46

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source=arxiv_source observed=2026-08-12T04:39:38.005253Z digest=sha256:9493bdf74835033b4dcae6fa2fb2a34013405199eceaf3052fd5f150ffe202f2

Observation d5f97176-7d1e-4511-b839-9e51a1396cfb · outbound

This paper cites Graded cellular bases for Temperley-Lieb algebras of type A and B.

Big data approach to Kazhdan-Lusztig polynomials Graded cellular bases for Temperley-Lieb algebras of type A and B

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-12T04:39:38.387275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.008418Z digest=sha256:a87c0073b28af475f560448d0adeab7d554478c81ce4fd4fe4b2d7b96dde835c

Observation a5721cec-7113-4568-b755-9f8bbb205e21 · outbound

This paper cites 2-Kac-Moody algebras.

Big data approach to Kazhdan-Lusztig polynomials 2-Kac-Moody algebras

Reference 48

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source=arxiv_source observed=2026-08-12T04:39:38.012566Z digest=sha256:91870a8bafe63c90329a410eaa693ac35202e2f85e6aedb5b0206fe9bbfeabfa

Observation dae061dd-4707-49a6-bb30-890280b1be39 · outbound

This paper cites u r die V alenztheorie geeignete B asis der bin \.

Big data approach to Kazhdan-Lusztig polynomials u r die V alenztheorie geeignete B asis der bin \

Reference 49

Resolution
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source=arxiv_source observed=2026-08-12T04:39:38.016092Z digest=sha256:e027466ad244b3b2d4f23fecb1fff19ed057b36e8120085356b8ff2fef3eda15

Observation eafa4006-219d-4baf-9555-425c6feee420 · outbound

This paper cites Russell and J.

Big data approach to Kazhdan-Lusztig polynomials Russell and J

Reference 50

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source=arxiv_source observed=2026-08-12T04:39:38.019789Z digest=sha256:d420048b6340ecb86929120fb9e023f709cdc3d7cf8c89fcba8187c64c527161

Observation c2481662-7a60-4fce-b7b4-2079676a77c0 · outbound

This paper cites The transition matrix between the Specht and web bases is unipotent with additional vanishing entries.

Big data approach to Kazhdan-Lusztig polynomials The transition matrix between the Specht and web bases is unipotent with additional vanishing entries

Reference 51

Resolution
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local_arxiv, observed 2026-08-12T04:39:38.361331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.023378Z digest=sha256:f7051d589ee283690af27ecb25fabce1e6386d3ebe4b6319099c020e5039c827

Observation a64b2a59-3ce8-4351-8286-2cd117fee3f2 · outbound

This paper cites Structure of the chromatic polynomial.

Big data approach to Kazhdan-Lusztig polynomials Structure of the chromatic polynomial

Reference 52

Resolution
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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.026979Z digest=sha256:81ae18d35223eebee4aae6eee4f84f0fba25f809d98042969d4af80d2e4bbd93

Observation bf1e17c1-398a-40b9-952e-136afe3a0648 · outbound

This paper cites Shapiro, M.

Big data approach to Kazhdan-Lusztig polynomials Shapiro, M

Reference 53

Resolution
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doi, observed 2026-08-12T04:39:38.144422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.030420Z digest=sha256:77f2b7a3f8c59a3da6f823d1b2a4334b1da60aab069215fa39b68079b6d124a0

Observation cad59107-212f-4aa8-9c47-2f931a2b3d03 · outbound

This paper cites Shepp and R.J.

Big data approach to Kazhdan-Lusztig polynomials Shepp and R.J

Reference 54

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doi, observed 2026-08-12T04:39:38.131243Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.033960Z digest=sha256:0fc02607a6eb27540a795b306430ac88fc9a2d2206bb7e9a5a34fb8b26543ae6

Observation b9950bcd-7587-4654-aa1f-e0bcb14e8b46 · outbound

This paper cites Singh, F.

Big data approach to Kazhdan-Lusztig polynomials Singh, F

Reference 55

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source=arxiv_source observed=2026-08-12T04:39:38.037852Z digest=sha256:840fb6ffe5c08bca1b98fbc5113e0ff4478d4c33ff83c73933c9a6dab582c357

Observation 4cd72b56-3a36-4b2c-bac7-7a56e1511d50 · outbound

This paper cites an unresolved cited work.

Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-08-12T04:39:38.041956Z digest=sha256:25c8253be821cd46c389b0c716d3ed85ffd1d588bd7fc93a4c972a0431219f4d

Observation 5a764410-afb7-4db0-a9e5-71af6fff0925 · outbound

This paper cites SL2 tilting modules in the mixed case.

Big data approach to Kazhdan-Lusztig polynomials SL2 tilting modules in the mixed case

Reference 57

Resolution
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source=arxiv_source observed=2026-08-12T04:39:38.045778Z digest=sha256:7460dfb3acd9a21d75398edfe3cfd908f6945a36a5221ff74759ccc83d0f6273

Observation 8faf00ec-bc09-4b0e-9b8a-285c481eebb4 · outbound

This paper cites Tamassia, editor.

Big data approach to Kazhdan-Lusztig polynomials Tamassia, editor

Reference 58

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raw_fallback, observed 2026-08-12T04:39:38.968028Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.049883Z digest=sha256:fb5b655eeea448e2be597b1e158ff69d26ab7dc2aaf44bf81b16d23b037a8065

Observation b9a7fb23-6f78-4a5c-9985-976140aa7952 · outbound

This paper cites Pattern Avoidance and the Bruhat Order.

Big data approach to Kazhdan-Lusztig polynomials Pattern Avoidance and the Bruhat Order

Reference 59

Resolution
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local_arxiv, observed 2026-08-12T04:39:38.318606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.053235Z digest=sha256:61c747818abd56f9c128b6aa5d9a65bcad2d4bf67c7cb13e219ee5451e2b6e36

Observation ef4c1fa1-dc0d-4883-98be-5948a2f1e856 · outbound

This paper cites On rank one 2-representations of web categories.

Big data approach to Kazhdan-Lusztig polynomials On rank one 2-representations of web categories

Reference 60

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source=arxiv_source observed=2026-08-12T04:39:38.057064Z digest=sha256:15704d7e5c22f3d68f682f7f3fe5f664617c5c1c28cb686097f65a10aaa86440

Observation 5aba532f-05d7-481a-94a4-f63f155f351d · outbound

This paper cites Equivalence classes for the mu-coefficient of Kazhdan-Lusztig polynomials in S_n.

Big data approach to Kazhdan-Lusztig polynomials Equivalence classes for the mu-coefficient of Kazhdan-Lusztig polynomials in S_n

Reference 61

Resolution
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local_arxiv, observed 2026-08-12T04:39:38.293967Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.060409Z digest=sha256:2850e2015020a3d8bcff6fa27b4a21d02a5bfe6f81a3fca17cb0455ec85ee974

Observation 51a79263-f9e1-46e2-a823-a990a5e78ea3 · outbound

This paper cites Weighted Khovanov-Lauda-Rouquier algebras.

Big data approach to Kazhdan-Lusztig polynomials Weighted Khovanov-Lauda-Rouquier algebras

Reference 62

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source=arxiv_source observed=2026-08-12T04:39:38.063806Z digest=sha256:1e957d3e3d39a31b97f374e0be0f90cf10437eb4886f485b8a1913649b48ce6a

Observation fe0d8362-401c-4d09-8697-0e3064b16ecb · outbound

This paper cites Is deep learning a useful tool for the pure mathematician?.

Big data approach to Kazhdan-Lusztig polynomials Is deep learning a useful tool for the pure mathematician?

Reference 63

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T04:39:38.067385Z digest=sha256:a3217a75971eb344b051f9380260ae9f27b93e86dea5efbddc78785612a9f776

Observation 0d14bc46-9118-42c4-a725-ac05a02714b6 · outbound

This paper cites Permutations with Kazhdan-Lusztig polynomial P_{id,w}(q) = 1 + q^h.

Big data approach to Kazhdan-Lusztig polynomials Permutations with Kazhdan-Lusztig polynomial P_{id,w}(q) = 1 + q^h

Reference 64

Resolution
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local_arxiv, observed 2026-08-12T04:39:38.256540Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.072340Z digest=sha256:99fa0ef3bead5d352f769dd0184cd8af331e59890d22c97147100f38afddff83

Observation 629d9d86-8076-41fe-ad44-e017634a86cc · outbound

This paper cites Zeroes of the Jones polynomial.

Big data approach to Kazhdan-Lusztig polynomials Zeroes of the Jones polynomial

Reference 65

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local_arxiv, observed 2026-08-12T04:39:38.239348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-12T04:39:38.075881Z digest=sha256:1fdcfdbe9a1a1c48f1e6922b5a5d2b82d44fe9efee204d842278f8c03dce014f

Observation 9b62d670-ecd7-470f-9194-2ac343dcfe5f · outbound

This paper cites an unresolved cited work.

Big data approach to Kazhdan-Lusztig polynomials Unresolved cited work

Reference 66

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source=arxiv_source observed=2026-08-12T04:39:38.080525Z digest=sha256:abaeb90fe99cc466c1027c4f19484193dc818dc6995c5d2c145a9566c9e69f1a

Pith citing papers

No inbound Pith citation observations are available.