Paper Citation Record · LEDGER

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

As of 10 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 8 inbound Pith citation observations for arXiv:2505.20161.

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

pith.paper-citation-record.v1
2505.20161 v2

Coverage vector

measured 100 of 103 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:04:24.297640Z

measured 108 of 108 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:01:18.854942Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:28:38.253948Z

Reference resolution

100 of 103 outbound references displayed

verified exact1
verified fuzzy43
unresolved56
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a16b10e8-ec5b-4b79-a6ba-302b79ada5b7 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:14.668962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8e5ec98-ed25-4c2f-87fa-4c0ad687cf69 · outbound

This paper cites Bukharin, S.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Bukharin, S

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:14.808481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95337c4c-41dd-4112-962b-c45e9f14dd7d · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:14.904017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b348d506-8c80-4c7f-b71b-5c0f00ff0a24 · outbound

This paper cites Cobbe, V.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Cobbe, V

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.008390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e8124a0-8c06-4c4f-abb0-fb18a7670749 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.126409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00946eaf-932f-49cc-9862-13758287c3da · outbound

This paper cites Didolkar, A.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Didolkar, A

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.211800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7325760a-30b0-42c3-9bf6-a23fd48c0376 · outbound

This paper cites Fourrier, N.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Fourrier, N

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.289884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d410004a-34cc-4de6-8cf4-e2c99f4327ce · outbound

This paper cites Friedman and A.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Friedman and A

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.390764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ee70049-fa19-4855-87d4-0c44bf51d6c5 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.462098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 691496fe-18d3-4550-a38d-593cc2e69f79 · outbound

This paper cites Gunasekar, Y.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Gunasekar, Y

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.540749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a23785c-3feb-4a14-b584-1cf87136455d · outbound

This paper cites Havrilla, A.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Havrilla, A

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.660125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95b1a35a-98d0-4cc8-95a8-ce866a774cc6 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.782728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24af5e89-777a-4038-9b32-d079b1746a35 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:15.883005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81ab8558-78dc-4cd5-86b0-b21354b55387 · outbound

This paper cites Hendrycks, C.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Hendrycks, C

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.000144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2debda60-07f7-41dc-9c14-0aa2a8332b95 · outbound

This paper cites Hendrycks, C.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Hendrycks, C

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.122962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78cb38a0-c4f4-4fd0-be13-e3d9e0a4f6a7 · outbound

This paper cites Open r1: A fully open reproduction of deepseek-r1, January 2025.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Open r1: A fully open reproduction of deepseek-r1, January 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.231786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dc2e22a-ea8e-413f-a1ae-22c2d2eeee72 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.353951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09a6322e-ccee-4c0c-b35c-a316257f60e6 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.450156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73d3c7c5-4678-41af-8bea-656e59d888b5 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.574795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fa61409-6bd0-45e2-9b59-e3d94ef88bf3 · outbound

This paper cites Killamsetty, S.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Killamsetty, S

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.674661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62d606a3-dfdb-40dd-9d5a-3906397e90b4 · outbound

This paper cites Killamsetty, D.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Killamsetty, D

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.770000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2247335f-f9cd-48f7-b70c-ed920fea2a88 · outbound

This paper cites Lewkowycz, A.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Lewkowycz, A

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.870009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eb78c33-7aa3-429e-aec7-ed32dff7b9f2 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:16.967093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10536fc5-99e7-46f9-84db-28252ca9865f · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:17.038908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5da43d-6f51-440f-9d4d-e5bb5f41adbe · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:17.101016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1de993a5-652a-4f1b-b74a-bcec8941c233 · outbound

This paper cites Lightman, V.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Lightman, V

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:37.850055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation becd734d-37a3-4559-8446-a1da5ac39268 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:37.670821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aee9d6be-0f6b-46e5-bb7f-a6e97693c141 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:37.459037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b2a1872-07bc-4b3e-9a60-b3a456323df5 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:37.286650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 16fbe2e4-b30a-4279-922b-40bbec5e4024 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:37.076072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a34c262e-3bca-4a3a-897e-de833b2875b7 · outbound

This paper cites The llama 3 herd of models, 2024.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning The llama 3 herd of models, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:36.871159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 136a2a10-decb-4417-8701-eff5bafd57d6 · outbound

This paper cites Longpre, L.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Longpre, L

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:36.725947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c64bdc70-8b3e-4a4b-a57b-107bcd196715 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:18.081487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29f7745d-2ccb-4e71-8772-a12038057575 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:36.557812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dcb4b0ea-29ce-4936-a9d6-a4a33fdd7f47 · outbound

This paper cites Maharana, P.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Maharana, P

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:36.371383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 53ba4e86-f58f-470d-a1cf-e7cd5177b426 · outbound

This paper cites Maini, S.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Maini, S

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:36.212843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 15c8f993-ab03-4e88-b1b0-194e29bb1d25 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:35.991402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ef086429-5acb-474b-b56e-d328b83fb82e · outbound

This paper cites Mirzasoleiman, J.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Mirzasoleiman, J

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:35.856628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f37185a9-f85a-49f3-a22e-abcf30d00f45 · outbound

This paper cites Muennighoff, N.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Muennighoff, N

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:18.721971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cce7e43-de99-4188-b270-2431882064f1 · outbound

This paper cites Muennighoff, Z.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Muennighoff, Z

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:35.637956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74e4d360-65ed-4b75-8c7c-361f222056dc · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:35.501225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5dc16bb6-3264-45c7-9baf-f03284e01fdd · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:35.275237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1dac699d-9c1c-4a43-8c43-d90f38bc59ba · outbound

This paper cites Gpt-4 technical report, 2024.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Gpt-4 technical report, 2024

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:19.113217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 275416d7-0ab6-4876-b550-ce50687f2cde · outbound

This paper cites Open Thoughts.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Open Thoughts

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:35.107109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fd0ac988-d50f-4687-a12a-bf106ee6bbe1 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 45

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e82dae4d-c149-4fa3-94ad-5c0b56c60a60 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:34.719357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3b6132a8-a2f2-4f26-9a53-ae94748bf25b · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:34.548937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 41a6e96e-c75f-4f0c-bc63-dfabcc733d47 · outbound

This paper cites Pruthi, F.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Pruthi, F

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:34.392721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 45b24875-d84a-494b-abeb-a1a03e8396b7 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:19.566446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 112ec162-9187-4c29-8404-9cfdeaa24950 · outbound

This paper cites Tensorized Random Projections.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Tensorized Random Projections

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:04:24.716696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1967aba-af7f-4616-8b2a-65d005f4864f · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:34.231849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d09bd8a-5c3a-428b-87d1-60b424a1492a · outbound

This paper cites Large Language Models Can Be Easily Distracted by Irrelevant Context.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Large Language Models Can Be Easily Distracted by Irrelevant Context

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:19.830002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76a3704b-0dce-4711-960e-121c11fe4704 · outbound

This paper cites Srivastava, A.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Srivastava, A

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:33.960510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a888c636-e708-4634-b212-295ff85021e5 · outbound

This paper cites Toshniwal, W.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Toshniwal, W

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:33.792056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 98424954-3d32-422d-a76d-fc80754ce722 · outbound

This paper cites Vendrow, E.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Vendrow, E

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:33.559883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b0c1ff33-63cb-40e4-a9a8-02f663435d00 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:33.341992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5051845a-b0fa-4bfe-8507-9eb68abc0338 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:33.085317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 30d207ad-cbae-48ef-87b6-d9a97bdc03e7 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:32.925113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1269b4a8-e7f4-411a-adce-a15646d99413 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:32.704927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 551c89d0-e74e-421f-b3b6-9dcf9f77447d · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:32.470642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f36647aa-94e4-461f-948b-c0c31d12f8de · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:32.152827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6cb80489-f340-445f-b72f-bd66a1dfde95 · outbound

This paper cites Yang, W.-L.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Yang, W.-L

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:31.870172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 912e2784-3cfc-4c70-870d-4e8aca7a6b2f · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:31.507216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ce170a80-a5dd-483e-834a-829dc88afba7 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:31.171175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 70d3df7d-f72c-4620-a2cc-96932594c89e · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:31.004480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e32252f6-b8b4-4646-922c-fe484b9259b2 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:30.796257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation af504609-bb01-47e5-826e-b47c00af58f5 · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:30.638071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a305f983-c5da-45b3-970a-bb46675ea70b · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:30.474170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ad534e00-bba6-4403-ab3d-9a2436119c5a · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:30.302710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c841b80a-483f-49ce-848b-b56b0354c209 · outbound

This paper cites Zhang, J.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Zhang, J

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:30.172003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b0a085a2-7846-4c61-ba8b-c1b9a1f92aa3 · outbound

This paper cites Zhong, R.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Zhong, R

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:29.905292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e8e89677-2376-41cc-9767-9a684da7b22f · outbound

This paper cites an unresolved cited work.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:29.660096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 31997f4a-c310-46bf-884b-f1d29eb33421 · outbound

This paper cites This is given directly in the problem statement.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning This is given directly in the problem statement

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:29.434533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7c6ff351-d5b8-4c52-8f89-f50f45a9697e · outbound

This paper cites 23 Example 2 Original Sample Problem: The number of math problems that Marvin practiced today is three times as many as the number of problems he solved yesterday.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning 23 Example 2 Original Sample Problem: The number of math problems that Marvin practiced today is three times as many as the number of problems he solved yesterday

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:29.200512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7cfdabbf-b0d9-422b-ae2e-6ed8b903048d · outbound

This paper cites 24 Example 3 Original Sample Problem: The $4.55 in Carol’s piggy bank consists of quarters and nickels.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning 24 Example 3 Original Sample Problem: The $4.55 in Carol’s piggy bank consists of quarters and nickels

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:28.994840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b545b9f5-1788-4126-9322-d28e5970e475 · outbound

This paper cites Smallville.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Smallville

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:28.764010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 50c19d56-a87c-471c-9763-68451f74926b · outbound

This paper cites [omitted] Therefore, the total number of sticks the three boys need to collect is 129 sticks.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning [omitted] Therefore, the total number of sticks the three boys need to collect is 129 sticks

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:28.575836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 40fca6cf-07f2-425b-be74-4c31f703afe0 · outbound

This paper cites [omitted] Thus, the total number of stamps Bella bought is 38.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning [omitted] Thus, the total number of stamps Bella bought is 38

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:28.357421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fe086ded-4e8a-4983-b3fa-ca2df1847145 · outbound

This paper cites Problem: Rebecca makes her own earrings out of buttons, magnets, and gemstones.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Problem: Rebecca makes her own earrings out of buttons, magnets, and gemstones

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:28.122320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f2de0f11-6ea8-4370-9cd8-d8c4b66b6f9d · outbound

This paper cites 28 Math Example 2: Computing the remainder Problem: At the height of cranberry season, there are 60000 cranberries in a bog.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning 28 Math Example 2: Computing the remainder Problem: At the height of cranberry season, there are 60000 cranberries in a bog

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.945623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ece5bc27-0772-45a9-8193-90eb0c33d401 · outbound

This paper cites [omitted] Therefore, the number of cranberries left in the bog after being harvested by humans and eaten by elk is 16000 cranberries.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning [omitted] Therefore, the number of cranberries left in the bog after being harvested by humans and eaten by elk is 16000 cranberries

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.802290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 448accdc-691e-4911-949e-4220a06305b8 · outbound

This paper cites Problem: Out of 804 senior high school students, 75% passed their exams and so got their degree.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Problem: Out of 804 senior high school students, 75% passed their exams and so got their degree

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.720253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 61fefdba-7bad-4ba9-b0b6-6c7df7aa569b · outbound

This paper cites [omitted] Therefore, the number of students who didn’t pass their exams is 201 students.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning [omitted] Therefore, the number of students who didn’t pass their exams is 201 students

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.594600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8878f57d-b79d-401a-9307-725c1db39e1f · outbound

This paper cites [omitted] Therefore, Miranda saved $70 per month.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning [omitted] Therefore, Miranda saved $70 per month

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.458671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 30f38f57-0b50-4f72-aaa1-b9257ee778f3 · outbound

This paper cites Problem: In 5 years, Raven will be 4 times as old as Phoebe.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Problem: In 5 years, Raven will be 4 times as old as Phoebe

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.372796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 87f155bd-af8b-40a6-8627-27717c5ebcc4 · outbound

This paper cites Problem: After five years, Ron will be four times as old as Maurice.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Problem: After five years, Ron will be four times as old as Maurice

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.265114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 299d235b-d73f-49f5-9bd3-e505d01d3e25 · outbound

This paper cites 30 NeurIPS Paper Checklist.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning 30 NeurIPS Paper Checklist

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.179308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 32c15ef0-1c02-45b8-b6ea-d2ed245015b9 · outbound

This paper cites Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:27.058264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7c67063-d8a9-44e4-bc08-287a046b185f · outbound

This paper cites Limitations.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Limitations

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.956006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9c599505-1a7f-47cb-b7bd-92eb1fb10c8c · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include theoretical results.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not include theoretical results

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.882293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 22b3cff4-c8be-46f9-ac94-92a8481531c2 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not include experiments

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.767817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 58afa133-ccdb-4e82-9e13-ce65663ce9b0 · outbound

This paper cites Guidelines: • The answer NA means that paper does not include experiments requiring code.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that paper does not include experiments requiring code

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.662313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f4ca3e57-6ca5-4ffb-af8e-26190478fe02 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not include experiments

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.537228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56e296c0-7963-4f88-81de-93532fcd8d74 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not include experiments

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.362006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d925e5c-f74c-4d70-9d17-c6ac18b0c51b · outbound

This paper cites • The paper should indicate the type of compute workers CPU or GPU, internal cluster, or cloud provider, including relevant memory and storage.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning • The paper should indicate the type of compute workers CPU or GPU, internal cluster, or cloud provider, including relevant memory and storage

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.186656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 21b0f979-6be1-4aff-bbcb-30eb8258d01e · outbound

This paper cites Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:26.021097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 889dd345-9714-4633-bee5-0d3ecd9991f4 · outbound

This paper cites Guidelines: • The answer NA means that there is no societal impact of the work performed.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that there is no societal impact of the work performed

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:25.888428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1d7a6535-e7fe-49cd-8022-8520f7e13264 · outbound

This paper cites We did not scrape any internet data, and our models are narrowly trained on these specific tasks.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning We did not scrape any internet data, and our models are narrowly trained on these specific tasks

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:25.692488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 071dad74-c661-48e1-8c05-1d3c98e5ff0d · outbound

This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not use existing assets

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:25.594765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 38f7712c-af0d-4872-9f8e-4c9f0e03fab2 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not release new assets.

Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning Guidelines: • The answer NA means that the paper does not release new assets

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:25.435263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation abeab290-d4bd-4e9a-bfae-5add6b37d837 · inbound

Socratic-MCTS: Test-Time Visual Reasoning by Asking the Right Questions cites this paper.

Socratic-MCTS: Test-Time Visual Reasoning by Asking the Right Questions Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:18.854942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3cc08b3-62ba-4f0d-8dbe-175db9c5db1b · inbound

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

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T01:17:11.731180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b48b36f2-9a70-4362-a29c-792d668c2985 · inbound

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-21T01:20:33.057254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a091a82-a9c5-44d1-aff7-e862b6f7e324 · inbound

MARS$^2$: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation cites this paper.

MARS$^2$: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-21T01:20:33.057254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5ba2e6db-13d9-45b0-80af-bcdeec48ee89 · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-21T01:20:33.057254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b870cef4-ccf3-40fc-a101-1991cc8a7f90 · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T12:58:42.275860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2d3eba8-1198-4533-8338-a777a9110254 · inbound

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs cites this paper.

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-21T01:20:33.057254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eac1f9c0-3b26-4075-b5f2-75d7561f6d90 · inbound

Neuron-Aware Active Few-Shot Learning for LLMs cites this paper.

Neuron-Aware Active Few-Shot Learning for LLMs Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning

Reference 46

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