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Paper Citation Record · LEDGER

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 2 inbound Pith citation observations for arXiv:2505.22068.

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

pith.paper-citation-record.v1
2505.22068 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:22.761418Z

measured 48 of 48 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:55:22.768635Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

46 of 46 outbound references displayed

  • verified exact3
  • verified fuzzy7
  • unresolved36
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6a3f8e2f-e06c-4db9-bbb2-c245ab96de2c · outbound

This paper cites GPT-4 Technical Report.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO GPT-4 Technical Report

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:17.851292Z digest=sha256:9c931f9cdd26b886d63508a57c7e3b0248b7201562158ae43782027272f27661

Observation bd80d493-37c2-40d9-a7a3-840cc16515a7 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2

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source=pdf_text observed=2026-08-07T13:21:17.903852Z digest=sha256:280535ad26b9d3a813f2dbf07383b2f2bfae9bda82c81ed5417c887529910138

Observation 7ca393dc-3240-484f-820c-5427b2b5b067 · outbound

This paper cites SciBERT: A Pretrained Language Model for Scientific Text.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO SciBERT: A Pretrained Language Model for Scientific Text

Reference 3

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source=pdf_text observed=2026-08-07T13:21:18.036986Z digest=sha256:69659debaa4615916aa987fc02f643a0cf05e7489452330f61021b22948dd940

Observation 2341ff3e-793d-4a1a-aeab-6dc2b8133375 · outbound

This paper cites Codekgc: Code language model for generative knowledge graph construction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Codekgc: Code language model for generative knowledge graph construction

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:25.448870Z

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.

source=pdf_text observed=2026-08-07T13:21:18.113341Z digest=sha256:ce1740d28b6db0f2ddde50484b1156e740b3e8c5c254af99132bb41755d56d3a

Observation 04573047-e383-4f8b-ba2f-79c16b3468fd · outbound

This paper cites Language models are few-shot learners.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Language models are few-shot learners

Reference 5

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source=pdf_text observed=2026-08-07T13:21:18.211283Z digest=sha256:73de8f5f6045594c5b4ca51081bea642d4cd4046fe3ce2baf00ae06925c41abe

Observation 91bcd34b-8f7f-4b2b-8100-ea520b5399ba · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 6

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source=pdf_text observed=2026-08-07T13:21:18.285802Z digest=sha256:3d5a3d1ce15178d7f229a77def7b245c8d66ff118ae13035b60a919f299fdde7

Observation e4e00c76-b301-4b5a-8b76-f579a794ac1b · outbound

This paper cites Scaling instruction-finetuned language models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Scaling instruction-finetuned language models

Reference 7

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source=pdf_text observed=2026-08-07T13:21:18.365373Z digest=sha256:e221d7c5330b33f3f912bd65af8ec7c9662ca9129aaca295cf0376092e90149a

Observation ec74b80f-6946-4fc0-9d9b-e2ad5249f325 · outbound

This paper cites Structured information extraction from scientific text with large language models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Structured information extraction from scientific text with large language models

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:25.317141Z

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.

source=pdf_text observed=2026-08-07T13:21:18.448507Z digest=sha256:3018bd254486244f3225ef48155a3cfc75353d238da9022e93ad52f203f972b7

Observation 3ba9158f-3c1d-4e4f-913c-7d9c53c918b3 · outbound

This paper cites Gemini 2.0 flash thinking„ 2024.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Gemini 2.0 flash thinking„ 2024

Reference 9

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raw_fallback, observed 2026-08-07T13:21:25.139098Z

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.

source=pdf_text observed=2026-08-07T13:21:18.541170Z digest=sha256:b298dfb4cb594e06f4a49cd7af18942ca82e07d654f128b1e9349cf7d3191c44

Observation 81a27feb-74a8-4a7a-96fe-e8fb2f0c3392 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 10

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source=pdf_text observed=2026-08-07T13:21:18.697037Z digest=sha256:49e2ac7b4b60ebfa07265fd489a3d840bb4e7dd57159a6b93fbcf3f6f1845fc8

Observation 13dec200-0d14-48b3-96be-be1c4cf7a765 · outbound

This paper cites Competitive Programming with Large Reasoning Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Competitive Programming with Large Reasoning Models

Reference 11

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source=pdf_text observed=2026-08-07T13:21:18.875663Z digest=sha256:2bd6eb1150d4b34bb28af39129dadfea89c20d1ccde312aa2c4110fb444c9ce3

Observation 7e0a3644-951e-467f-a446-214c0ebd8069 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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source=pdf_text observed=2026-08-07T13:21:18.994514Z digest=sha256:df2b2355bfcd7af0f481f02e03a12d588a87786361aaa282f81368b8316a9431

Observation 659cf4d1-57a4-4519-b01b-e0d923780aac · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Distilling the Knowledge in a Neural Network

Reference 13

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source=pdf_text observed=2026-08-07T13:21:19.081057Z digest=sha256:b1b63277f82d1b470c6c27361b81dd98d9893883f5806a5200d696719baf6981

Observation 18924d5b-a9d3-469a-8511-f19d5b197149 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Training Compute-Optimal Large Language Models

Reference 14

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source=pdf_text observed=2026-08-07T13:21:19.159809Z digest=sha256:f71fa8c300dae794ae1f78a165414e3a2ee7fa4a3f4f15606103deb8ab87d21d

Observation 14e1bd0d-0391-4816-98b5-7065283ce54c · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Lora: Low-rank adaptation of large language models

Reference 15

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source=pdf_text observed=2026-08-07T13:21:19.256717Z digest=sha256:264575567f27889365e8db0f6c5241cf5675b5bc88044241693f6841da070634

Observation 2bad962b-a4c0-4032-b2cd-6819a4681f28 · outbound

This paper cites OpenAI o1 System Card.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO OpenAI o1 System Card

Reference 16

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source=pdf_text observed=2026-08-07T13:21:19.379751Z digest=sha256:c083f5259491871f10afff22dac0e899f58b05bd37bb1dfd1eb02ae31b4757ed

Observation 40f1b00d-9b0b-4b32-9bbb-e9947080bd6a · outbound

This paper cites Scaling Laws for Neural Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Scaling Laws for Neural Language Models

Reference 17

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source=pdf_text observed=2026-08-07T13:21:19.424609Z digest=sha256:0ef4e8e4015c433da9d1c1cbaeedea72b6a6f612e7b945e5db839300bf625cad

Observation b38defa1-fe24-4b5c-a4d9-92b76c4a108d · outbound

This paper cites LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Reference 18

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source=pdf_text observed=2026-08-07T13:21:19.506483Z digest=sha256:0c4e80132920d98f915e0dcdc186f941c3ab7cccbbfc0e72c4f6b36f90cda888

Observation de0020d1-3bd6-4cf7-8a3d-535e121a91a9 · outbound

This paper cites Revisiting Large Language Models as Zero-shot Relation Extractors.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 19

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source=pdf_text observed=2026-08-07T13:21:19.586236Z digest=sha256:4b57281319d1275c6a817e50141689bb6e7589458da9f9a170102ee039c81087

Observation c03ba290-79dc-4038-b887-e61deeb04c8c · outbound

This paper cites Getting more juice out of the sft data: Reward learning from human demonstration improves sft for llm alignment.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Getting more juice out of the sft data: Reward learning from human demonstration improves sft for llm alignment

Reference 20

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raw_fallback, observed 2026-08-07T13:21:24.994412Z

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.

source=pdf_text observed=2026-08-07T13:21:19.724379Z digest=sha256:fb1179eceb8fec6d836a40ccc6b9e58740280856a953bf923a2227e96a197678

Observation 49c73c6d-ccb6-4c18-916d-4f0226acd760 · outbound

This paper cites PIVOINE: Instruction Tuning for Open-world Information Extraction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO PIVOINE: Instruction Tuning for Open-world Information Extraction

Reference 21

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local_arxiv, observed 2026-08-07T13:21:23.850092Z

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.

source=pdf_text observed=2026-08-07T13:21:19.779256Z digest=sha256:d1ac53d20e2f42b108af242c818eb11cb1079d8525cd1f4eef3ff7ba6b734b25

Observation 2f81de1e-9824-4510-89c4-b7fe78a72d13 · outbound

This paper cites UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction

Reference 22

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source=pdf_text observed=2026-08-07T13:21:19.858040Z digest=sha256:50be97128bd3db900fcbcdf0923889d1d4c6b8e725ca271862beeb20d18ac6b6

Observation eae0750a-8d9d-4174-8624-7ca4861b8292 · outbound

This paper cites Using of jaccard coefficient for keywords similarity.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Using of jaccard coefficient for keywords similarity

Reference 23

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:21:19.969120Z digest=sha256:162867f9e81b177ba021c6377b136a5c092e3021100ef46fc18621a8238bba85

Observation 2ec4d59b-088c-48a0-a96d-203b6f570785 · outbound

This paper cites Training language models to follow instructions with human feedback.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Training language models to follow instructions with human feedback

Reference 24

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source=pdf_text observed=2026-08-07T13:21:20.115279Z digest=sha256:9af9b732045019f8baa52b1e9fc277f6f3006886d9cd3f78835acc6900d408e4

Observation 304425f7-a6b1-4abe-935a-c3b3cf361ed0 · outbound

This paper cites Improving language understanding by generative pre-training.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Improving language understanding by generative pre-training

Reference 25

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source=pdf_text observed=2026-08-07T13:21:20.160573Z digest=sha256:98452da7700769ec2c8305a27d1c2ba763fbe33c1e4415050432f3545d9923fa

Observation cc743bff-5d00-479f-ba35-297247534e6f · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 26

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source=pdf_text observed=2026-08-07T13:21:20.300576Z digest=sha256:92854402c5be34bce689173e8381486d6cdd39bf45b984ae700327a74ef3b708

Observation c824a449-c453-44d9-a3ce-d7b91e5650fd · outbound

This paper cites To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Reference 27

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source=pdf_text observed=2026-08-07T13:21:20.484755Z digest=sha256:b164e43face07637a94b8a170935971ef061e4ac28248fe6b072febae3104126

Observation a7c92e83-a342-43c9-a744-63c7090173fc · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 28

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source=pdf_text observed=2026-08-07T13:21:20.594132Z digest=sha256:a3f48b826d2339918896502081b81276ed2681e5a3e9fa24e2a39a983f6e522d

Observation 8b204b30-57b2-4336-b42c-8b91c747260d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO LLaMA: Open and Efficient Foundation Language Models

Reference 29

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source=pdf_text observed=2026-08-07T13:21:20.690010Z digest=sha256:c7986f35fcc743cb73b3ef684af91a9385cc3365c4e2e5518ecd79af56ea312a

Observation f2ab7f53-c5b5-4531-a70a-238b91a2991d · outbound

This paper cites GPT-NER: Named Entity Recognition via Large Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO GPT-NER: Named Entity Recognition via Large Language Models

Reference 30

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source=pdf_text observed=2026-08-07T13:21:20.801599Z digest=sha256:d88fd1736f9bcd663a9dcdc4baee652d616fbb9cb7ec8d6dfcafa1919bfdd705

Observation dfe30051-4830-412b-9905-500de8302b9f · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Finetuned Language Models Are Zero-Shot Learners

Reference 31

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source=pdf_text observed=2026-08-07T13:21:20.884237Z digest=sha256:0fe0ccbe35fd3c4aef3c7ea9afcd5233bd513c0e8e2ed9e23e1809051aa0dc3f

Observation 89187d1d-459b-4500-8d96-c63e4c9c971e · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Chain-of-thought prompting elicits reasoning in large language models

Reference 32

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source=pdf_text observed=2026-08-07T13:21:20.933984Z digest=sha256:4f846defa3c531e117a0b4cf47a540815e50ea8f42513e8e7a528405d90e3934

Observation ad9faa9e-cd34-4d34-904b-355b0f3a2737 · outbound

This paper cites Zero-shot information extraction via chatting with chatgpt.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Zero-shot information extraction via chatting with chatgpt

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:24.572520Z

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.

source=pdf_text observed=2026-08-07T13:21:20.982314Z digest=sha256:67abc5dd1cdb48927bad32407c8e6941456a772ecca7d6319c94e7980f9b952e

Observation 4c3fc912-cc2d-400e-a067-ef65e08273f8 · outbound

This paper cites Empirical Study of Zero-Shot NER with ChatGPT.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Empirical Study of Zero-Shot NER with ChatGPT

Reference 34

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source=pdf_text observed=2026-08-07T13:21:21.117394Z digest=sha256:70eb3b86bd1c7c661ef1f0207de7457915188f60bef867c98bfccf4f021a6c78

Observation 469f9c16-5ca2-4258-b505-8119ebb9e897 · outbound

This paper cites Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks

Reference 35

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local_arxiv, observed 2026-08-07T13:21:23.469358Z

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.

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Observation 94710506-682a-4d63-a2c8-038793012fe6 · outbound

This paper cites Qwen2.5 Technical Report.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Qwen2.5 Technical Report

Reference 36

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no resolver link, observed 2026-08-07T13:21:21.405550Z

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source=pdf_text observed=2026-08-07T13:21:21.405550Z digest=sha256:bdb6706385749bfe00f1fdbc37d8c24ed8ed59135289a5c209a7363eddd835ae

Observation be3678c0-6e28-485d-ad37-e37290279a75 · outbound

This paper cites Packed Levitated Marker for Entity and Relation Extraction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Packed Levitated Marker for Entity and Relation Extraction

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:21:23.216161Z

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.

source=pdf_text observed=2026-08-07T13:21:21.507010Z digest=sha256:d481ef1bd657490acfab0cb295cf71e3b3c8c1d50abfbe39ef773ddb3d0f8c29

Observation 9416ed9f-94b8-45ed-b018-00746d59ec93 · outbound

This paper cites Zero-shot Temporal Relation Extraction with ChatGPT.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Zero-shot Temporal Relation Extraction with ChatGPT

Reference 38

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no resolver link, observed 2026-08-07T13:21:21.628275Z

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Observation 537790ab-e959-47b1-a1d6-793e495383ce · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 39

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unresolved
no resolver link, observed 2026-08-07T13:21:21.782500Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:21:21.782500Z digest=sha256:2f103f05982a594cdf85d3277b14b34811009e977982a40509ce7a2a0423f181

Observation c11297b3-5917-4986-b901-15f9389e2c79 · outbound

This paper cites Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction

Reference 40

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unresolved
no resolver link, observed 2026-08-07T13:21:21.935101Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:21:21.935101Z digest=sha256:91c535f9fa158ca4e7b3951295a74ae9a2e4c10fbed9fe46ba6a3cfba3274222

Observation 5bab54fc-8d2f-4db2-a277-40f68e025fa1 · outbound

This paper cites SciER: An Entity and Relation Extraction Dataset for Datasets, Methods, and Tasks in Scientific Documents.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO SciER: An Entity and Relation Extraction Dataset for Datasets, Methods, and Tasks in Scientific Documents

Reference 41

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no resolver link, observed 2026-08-07T13:21:22.082131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:22.082131Z digest=sha256:a8cef181e08b016b21475cf03f41b1dbe5cd43b015c1465f13410c14bef1b252

Observation b2387e02-6315-423f-abc3-671ea91c3574 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO OPT: Open Pre-trained Transformer Language Models

Reference 42

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no resolver link, observed 2026-08-07T13:21:22.266304Z

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source=pdf_text observed=2026-08-07T13:21:22.266304Z digest=sha256:9618facfa7c25fdb71e2fe1a7d75a7d4337f93cb29e2c46e7ddb6ada89274d66

Observation 5e0fcd4c-b3a7-4634-a343-f3a26e281a97 · outbound

This paper cites A Frustratingly Easy Approach for Entity and Relation Extraction.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO A Frustratingly Easy Approach for Entity and Relation Extraction

Reference 43

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unresolved
no resolver link, observed 2026-08-07T13:21:22.412626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:22.412626Z digest=sha256:e9fc94a20cbe13803ddcc70fd4fd53368bf8e306034d90861631956b195ebce9

Observation 08bb0454-2613-47ab-b291-42997fe354c4 · outbound

This paper cites Lima: Less is more for alignment.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Lima: Less is more for alignment

Reference 44

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unresolved
no resolver link, observed 2026-08-07T13:21:22.522467Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:21:22.522467Z digest=sha256:734260a794505753cce98730e6ca37cce7350b255d4c2fde2cd5ddb8e9200480

Observation 7ad69383-1424-49d8-88f5-4444be72447c · outbound

This paper cites Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:24.323264Z

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.

source=pdf_text observed=2026-08-07T13:21:22.613541Z digest=sha256:77ef6ee1fc5f00ddecf1161e55d74db47d397ebe3324c434412fa1d1607d506b

Observation 273102a3-d6ec-4b48-a481-b753e4ab3b7e · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Fine-Tuning Language Models from Human Preferences

Reference 46

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no resolver link, observed 2026-08-07T13:21:22.761418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:22.761418Z digest=sha256:9a9d2b29e9bc85b9b3b0da9bff96a769478a605540e3d0e900e9a2e6d8248738

Pith citing papers

Observation 379a3b1b-3cb7-459c-a496-f166fe5ee36e · inbound

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction cites this paper.

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO

Reference 52

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verified exact
arxiv_id, observed 2026-05-08T17:23:40.406161Z

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.

source=pdf_text observed=2026-05-08T17:22:17.266351Z digest=sha256:ac5c5d69b386a64b1b2d1cb82e18beacea8a7707136e31056d3b3f79c9846fae

Observation 39cf0a59-5e35-438d-ad03-c352d175247f · inbound

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction cites this paper.

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO

Reference 52

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verified exact
arxiv_id, observed 2026-07-01T00:05:09.456610Z

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.

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