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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 17 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 2026-08-17T06:30:58.91139+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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source=pdf_text observed=2026-08-07T13:21:17.851292Z digest=sha256:223a87558db0c426cbad4a7677a60cab5f24369827e982165ec8bb1bff6a1649

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=sha256:7bfa142db64a80297876f1c457a1f0a6a2d1faef8839432426ab28abda3b14ea

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=sha256:10e728978dd2dcff574f8d855ff563e6ad616ba27fe08da6e2c606193c87770c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:18.113341Z digest=sha256:6f0a26e8b5e769e7a0099bc39fd268ef7287a78e253fd336eb1b7dc72730e376

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=sha256:9688bd31b65a3d99f8f8e38956d92323fb38213d954a295e985562fd2be874ba

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=sha256:5acf5927cd5267e306ca9d7d38f5b22bca58f8f7595189eab9f27f6b240687a7

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:b75f604c4e4093a571e166e8f18eae8f39cba26d56fac1226192e4dac7751972

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

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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:18.448507Z digest=sha256:a9a9633a800623c1d2fbfb3d93b87bea1e8a7faa097ca47cb74477b6d86588b7

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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verified fuzzy
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:18.541170Z digest=sha256:40187ca887e7e012161fdf13210545c96f4e547a77c502220fd406bca1ed154f

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:ab2df96e980b0af7d71d45e7cc53890597df03479dd3b6f3be3de530c0bf9f56

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=sha256:9ac7c45eadcb31279ea59570f0a9cc3ab2961da7a0f85d177acd2192ed7676c1

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:a7a2db7547d22925ca550d5dca93b6a148f5a0ef238b6ed36825d7a4dbf188b9

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:ba623015dda9d9bc88b0f8647e8aee1b35fab49625ce28edf1a39b6ed6611078

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:ea70a91c74ff0d11b0cb180d1476490f5ae3d9b818c574659171acb8f4c016da

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=sha256:7774ee14a7ab7b6b696794dea7cc089622e62d6b0c28871676823254cbb571f2

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=sha256:32693b3cb6d2ddfb3e7d9e5df93987f5087f63926f798535c7626a2a4fd51eee

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=sha256:6a1f7dfad636e7c94e34b3f7c6a595ac597bbac7cf7d571da19e8ce7dcef6371

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=sha256:9a9e573935f631aab9fdf2d96f243fe996a057381cf8eb0124d8b2210f16028d

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:dbc84efbd1fe2103f7c0ed167ecdff33cdcc541775d0f4b55d982cda6f63a831

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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verified fuzzy
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:19.724379Z digest=sha256:53bfd7e722c59a5e4d20893581bb22108ea646058e2907d8d097887af68acbf7

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

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

source=pdf_text observed=2026-08-07T13:21:19.779256Z digest=sha256:ef2c92b6f6957f4e56f2ff2d187dd1dabee5a29a0252186f385dbba3e8a69538

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=sha256:20b22e57cc7e4b8c0d12d958df1619acdfab964e18ea3c063e35e73c8d95ae03

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:19.969120Z digest=sha256:37d981393674986dfb6fa9c4f4f4c5b996fad497509808f4bedd226ee1eb227d

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=sha256:01f53599f9859dea736aec6218c3b215787a0eed98bc55fc746253432b1edcb0

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=sha256:48d6977bd766e7212f834329991cc7f31ea19bc6e49f3b0f300f0e982040b8ed

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:f70785274dfea5ce006202910035d2763231b5a4ed7b0a0ac76b6a60b56dd0e6

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=sha256:3b3680d1a54f1a712395b0b3293322fbcacbfbc69848c5d30174e38b1d69ca43

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=sha256:0cb96a78779773b4da4c2c02dedd1e940fe79abbbd768149d100834a759db275

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=sha256:100358080ab597370fc016592d775585981528656ee2d6896b5a52b8caf3af92

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=sha256:9f5d5f8b7ff91b2c4b4e63ddae796fd8aaeb1d8e389cd84f7e36724e0c526c84

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:bdc410f22d536f8bd1fa0cc11f12c85ed1b24c9381f97c415c43a0838c6c743f

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:c6ad2990b09e67f3a0ffa496ff460a13588aed6e588921632c3ae2da5384ab13

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:20.982314Z digest=sha256:881967f442aa86324ea75f3753cdff2a1a3e74a0f43444df9c1bf46ec299798d

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:21.117394Z digest=sha256:9a0126da5be5c362b4b83d5c5425b51f687691489ea1de12bb6b262085b24ed8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:21.251678Z digest=sha256:4a110b6b9e0a3b118beb592dab1d270ec7d5df2e39642bba2e52a646937888f0

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:21.405550Z digest=sha256:4260511279b1ca12f0ed520a17c12b0dd7fd9d2bcacf3fa39b829c363830c89b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:21.507010Z digest=sha256:f88c00403f431729575a40350d362b1afd9873050261a6202412e96010d7f3c0

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

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:21:21.628275Z digest=sha256:510901490647044abe2e2a05172d244c9896956e8ad48812dbef5289e8d2e2b6

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

Resolution
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=sha256:88d50795ce67758435e8bbf3b7b8dec95b7bbf6d1b2f50ece7e62e1e40dbdbfb

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:21.935101Z digest=sha256:be0fe367eb76c0e0a6294dac5bfb0ed464597519c28407e5323a887f840d7dfe

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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unresolved
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:bd37bfba3a21eefc811fc5a20341e5935e3dd2a0b3a7345c949312cb7817977e

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:22.266304Z digest=sha256:7c1a43d138f276799522a84734b952fd4233a8c9ef298f7ac408b11a499e5aff

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

Resolution
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=sha256:8c3566eab9ec4284a5cd79ad9dadae5750d77cb9b66a1128329c5d5ca8108dc3

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:22.522467Z digest=sha256:38790901889d871880f5f3ce9a39c1a6b5552ab206ca4acb8532a64e1017116f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:21:22.613541Z digest=sha256:cf96513ac4d8fb8b8bda2f0f8d54e72b77b4eb1d506f1294c2584f3f341d6bac

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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unresolved
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=sha256:44cedab44e81c5237b6e33a694631158fd88b51d65373e409392b1e1b11cee01

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

Resolution
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-08T17:22:17.266351Z digest=sha256:28b177f303552ea6f63c3a6b88f180a5af255d5f00d169d5c884d0a8eff29a4d

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

Resolution
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T23:55:22.768635Z digest=sha256:04c3594d6f4f4562a57fdf7111841c5145849575d8e2260d0e3d5f6e86347a77