Evaluation of Finetuned LLMs in AMR Parsing | Paper Citation Record

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This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Evaluation of Finetuned LLMs in AMR Parsing Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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This paper cites Llama3/ M O D E L \_ C A R D .md at main · meta-llama/llama3 --- github.com.

Evaluation of Finetuned LLMs in AMR Parsing Llama3/ M O D E L \_ C A R D .md at main · meta-llama/llama3 --- github.com

Reference 2

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This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

Evaluation of Finetuned LLMs in AMR Parsing GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 3

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This paper cites SEMA: an Extended Semantic Evaluation Metric for AMR.

Evaluation of Finetuned LLMs in AMR Parsing SEMA: an Extended Semantic Evaluation Metric for AMR

Reference 4

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This paper cites Abstract meaning representation parsing for the Brazilian Portuguese language.

Evaluation of Finetuned LLMs in AMR Parsing Abstract meaning representation parsing for the Brazilian Portuguese language

Reference 5

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This paper cites Online Back-Parsing for AMR-to-Text Generation.

Evaluation of Finetuned LLMs in AMR Parsing Online Back-Parsing for AMR-to-Text Generation

Reference 6

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This paper cites AMR parsing using stack- LSTM s.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing using stack- LSTM s

Reference 7

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This paper cites A bstract M eaning R epresentation for sembanking.

Evaluation of Finetuned LLMs in AMR Parsing A bstract M eaning R epresentation for sembanking

Reference 8

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This paper cites One spring to rule them both: Symmetric amr semantic parsing and generation without a complex pipeline.

Evaluation of Finetuned LLMs in AMR Parsing One spring to rule them both: Symmetric amr semantic parsing and generation without a complex pipeline

Reference 9

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This paper cites Lukin, Stephen Tratz, Matthew Marge, Ron Artstein, David Traum, and Clare Voss.

Evaluation of Finetuned LLMs in AMR Parsing Lukin, Stephen Tratz, Matthew Marge, Ron Artstein, David Traum, and Clare Voss

Reference 10

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This paper cites Spatial AMR : Expanded spatial annotation in the context of a grounded M inecraft corpus.

Evaluation of Finetuned LLMs in AMR Parsing Spatial AMR : Expanded spatial annotation in the context of a grounded M inecraft corpus

Reference 11

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This paper cites Squib: Expressive power of abstract meaning representations.

Evaluation of Finetuned LLMs in AMR Parsing Squib: Expressive power of abstract meaning representations

Reference 12

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This paper cites S match: an evaluation metric for semantic feature structures.

Evaluation of Finetuned LLMs in AMR Parsing S match: an evaluation metric for semantic feature structures

Reference 13

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This paper cites Cohen, and Giorgio Satta.

Evaluation of Finetuned LLMs in AMR Parsing Cohen, and Giorgio Satta

Reference 14

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This paper cites A bstract M eaning R epresentations for S embanking.

Evaluation of Finetuned LLMs in AMR Parsing A bstract M eaning R epresentations for S embanking

Reference 15

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

Evaluation of Finetuned LLMs in AMR Parsing DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

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This paper cites Text Summarization using Abstract Meaning Representation.

Evaluation of Finetuned LLMs in AMR Parsing Text Summarization using Abstract Meaning Representation

Reference 17

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This paper cites Multilingual AMR -to-text generation.

Evaluation of Finetuned LLMs in AMR Parsing Multilingual AMR -to-text generation

Reference 18

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Evaluation of Finetuned LLMs in AMR Parsing Unresolved cited work

Reference 19

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This paper cites Smith, and Jaime Carbonell.

Evaluation of Finetuned LLMs in AMR Parsing Smith, and Jaime Carbonell

Reference 20

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This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Evaluation of Finetuned LLMs in AMR Parsing Gemma 2: Improving Open Language Models at a Practical Size

Reference 21

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This paper cites AMR parsing is far from solved: G r APES , the granular AMR parsing evaluation suite.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing is far from solved: G r APES , the granular AMR parsing evaluation suite

Reference 22

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This paper cites Unsloth: 2-5x faster llm fine-tuning with 70\ https://unsloth.ai/introducing, 2024.

Evaluation of Finetuned LLMs in AMR Parsing Unsloth: 2-5x faster llm fine-tuning with 70\ https://unsloth.ai/introducing, 2024

Reference 23

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This paper cites Nguyen, Dzung T.

Evaluation of Finetuned LLMs in AMR Parsing Nguyen, Dzung T

Reference 24

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This paper cites Training Compute-Optimal Large Language Models.

Evaluation of Finetuned LLMs in AMR Parsing Training Compute-Optimal Large Language Models

Reference 25

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

Evaluation of Finetuned LLMs in AMR Parsing Lora: Low-rank adaptation of large language models

Reference 26

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This paper cites Voss, Jiawei Han, and Avirup Sil.

Evaluation of Finetuned LLMs in AMR Parsing Voss, Jiawei Han, and Avirup Sil

Reference 27

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This paper cites D atasets --- huggingface.co.

Evaluation of Finetuned LLMs in AMR Parsing D atasets --- huggingface.co

Reference 28

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This paper cites S upervised F ine-tuning T rainer --- huggingface.co.

Evaluation of Finetuned LLMs in AMR Parsing S upervised F ine-tuning T rainer --- huggingface.co

Reference 29

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This paper cites O n the C omplexity of S equence to G raph A lignment --- link.springer.com.

Evaluation of Finetuned LLMs in AMR Parsing O n the C omplexity of S equence to G raph A lignment --- link.springer.com

Reference 30

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This paper cites Generalized shortest-paths encoders for AMR -to-text generation.

Evaluation of Finetuned LLMs in AMR Parsing Generalized shortest-paths encoders for AMR -to-text generation

Reference 31

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This paper cites Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention.

Evaluation of Finetuned LLMs in AMR Parsing Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Reference 32

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This paper cites Abstract meaning representation ( AMR ) annotation release 3.0, 2020.

Evaluation of Finetuned LLMs in AMR Parsing Abstract meaning representation ( AMR ) annotation release 3.0, 2020

Reference 33

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This paper cites Neural AMR : Sequence-to-sequence models for parsing and generation.

Evaluation of Finetuned LLMs in AMR Parsing Neural AMR : Sequence-to-sequence models for parsing and generation

Reference 34

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This paper cites A bstract M eaning R epresentation ( A M R ) A nnotation R elease 3.0 - L inguistic D ata C onsortium --- catalog.ldc.upenn.edu.

Evaluation of Finetuned LLMs in AMR Parsing A bstract M eaning R epresentation ( A M R ) A nnotation R elease 3.0 - L inguistic D ata C onsortium --- catalog.ldc.upenn.edu

Reference 35

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This paper cites P apers with C ode - L D C 2020 T 02 B enchmark ( A M R P arsing) --- paperswithcode.com.

Evaluation of Finetuned LLMs in AMR Parsing P apers with C ode - L D C 2020 T 02 B enchmark ( A M R P arsing) --- paperswithcode.com

Reference 36

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This paper cites Maximum B ayes S match ensemble distillation for AMR parsing.

Evaluation of Finetuned LLMs in AMR Parsing Maximum B ayes S match ensemble distillation for AMR parsing

Reference 37

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This paper cites Cross-media structured common space for multimedia event extraction.

Evaluation of Finetuned LLMs in AMR Parsing Cross-media structured common space for multimedia event extraction

Reference 38

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This paper cites Abstract Meaning Representation for Multi-Document Summarization.

Evaluation of Finetuned LLMs in AMR Parsing Abstract Meaning Representation for Multi-Document Summarization

Reference 39

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Evaluation of Finetuned LLMs in AMR Parsing Unresolved cited work

Reference 40

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This paper cites AMR parsing as graph prediction with latent alignment.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing as graph prediction with latent alignment

Reference 41

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This paper cites Cohen, and Ivan Titov.

Evaluation of Finetuned LLMs in AMR Parsing Cohen, and Ivan Titov

Reference 42

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This paper cites GPT -too: A language-model-first approach for AMR -to-text generation.

Evaluation of Finetuned LLMs in AMR Parsing GPT -too: A language-model-first approach for AMR -to-text generation

Reference 43

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This paper cites Rewarding S match: Transition-based AMR parsing with reinforcement learning.

Evaluation of Finetuned LLMs in AMR Parsing Rewarding S match: Transition-based AMR parsing with reinforcement learning

Reference 44

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This paper cites D oc AMR : Multi-sentence AMR representation and evaluation.

Evaluation of Finetuned LLMs in AMR Parsing D oc AMR : Multi-sentence AMR representation and evaluation

Reference 45

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This paper cites SMATCH ++: Standardized and extended evaluation of semantic graphs.

Evaluation of Finetuned LLMs in AMR Parsing SMATCH ++: Standardized and extended evaluation of semantic graphs

Reference 46

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This paper cites Better S match = better parser? AMR evaluation is not so simple anymore.

Evaluation of Finetuned LLMs in AMR Parsing Better S match = better parser? AMR evaluation is not so simple anymore

Reference 47

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This paper cites AMR similarity metrics from principles.

Evaluation of Finetuned LLMs in AMR Parsing AMR similarity metrics from principles

Reference 48

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This paper cites A bstract M eaning R epresentation of T urkish.

Evaluation of Finetuned LLMs in AMR Parsing A bstract M eaning R epresentation of T urkish

Reference 49

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This paper cites A M R P arsing W ith C ache T ransition S ystems | P roceedings of the A A A I C onference on A rtificial I ntelligence --- ojs.aaai.org.

Evaluation of Finetuned LLMs in AMR Parsing A M R P arsing W ith C ache T ransition S ystems | P roceedings of the A A A I C onference on A rtificial I ntelligence --- ojs.aaai.org

Reference 50

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This paper cites Graph-based approaches to text generation.

Evaluation of Finetuned LLMs in AMR Parsing Graph-based approaches to text generation

Reference 51

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This paper cites S em B leu: A robust metric for AMR parsing evaluation.

Evaluation of Finetuned LLMs in AMR Parsing S em B leu: A robust metric for AMR parsing evaluation

Reference 52

Resolution: verified exact; doi, observed 2026-08-05T23:41:57.008379Z

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This paper cites AMR -to-text generation as a traveling salesman problem.

Evaluation of Finetuned LLMs in AMR Parsing AMR -to-text generation as a traveling salesman problem

Reference 53

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.994445Z

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This paper cites A graph-to-sequence model for AMR -to-text generation.

Evaluation of Finetuned LLMs in AMR Parsing A graph-to-sequence model for AMR -to-text generation

Reference 54

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.980221Z

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

Observation 0fc17016-8fa8-4534-9557-5e56f82b3141 · outbound

This paper cites Semantic neural machine translation using AMR.

Evaluation of Finetuned LLMs in AMR Parsing Semantic neural machine translation using AMR

Reference 55

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.965964Z

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Observation bde9fab7-3de1-495f-9a64-7c8801777800 · outbound

This paper cites Overtrained language models are harder to fine-tune.

Evaluation of Finetuned LLMs in AMR Parsing Overtrained language models are harder to fine-tune

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:41:58.925496Z

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Observation 2bc3e376-9fc2-4183-9a4c-48e6bf453d04 · outbound

This paper cites Towards smaller, faster decoder-only transformers: Architectural variants and their implications.

Evaluation of Finetuned LLMs in AMR Parsing Towards smaller, faster decoder-only transformers: Architectural variants and their implications

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:41:57.929051Z

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Observation 455b8378-3e83-4c3d-b345-f97b2199d058 · outbound

This paper cites Cohen, and Mark Steedman.

Evaluation of Finetuned LLMs in AMR Parsing Cohen, and Mark Steedman

Reference 58

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.950959Z

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Observation c7223eea-bccf-4b9f-bb93-95d1ed8d6ebb · outbound

This paper cites Post-training 4-bit quantization of deep neural networks.

Evaluation of Finetuned LLMs in AMR Parsing Post-training 4-bit quantization of deep neural networks

Reference 59

Resolution: verified exact; raw_fallback, observed 2026-08-05T23:41:57.851073Z

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Observation 1938bdb9-f5f2-4fa2-929c-50039a5c9250 · outbound

This paper cites Neural headline generation on A bstract M eaning R epresentation.

Evaluation of Finetuned LLMs in AMR Parsing Neural headline generation on A bstract M eaning R epresentation

Reference 60

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.935204Z

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Observation 8e379ea2-9cc8-4a3d-aae1-38809a2f85e4 · outbound

This paper cites Attention Is All You Need.

Evaluation of Finetuned LLMs in AMR Parsing Attention Is All You Need

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T23:41:56.728850Z

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Observation 5e9eea62-d12a-4ed7-971f-60557bee5dfe · outbound

This paper cites an unresolved cited work.

Evaluation of Finetuned LLMs in AMR Parsing Unresolved cited work

Reference 62

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.920156Z

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Observation 3530fbc0-5d7b-4ca2-8e89-b0180186f470 · outbound

This paper cites A transition-based algorithm for AMR parsing.

Evaluation of Finetuned LLMs in AMR Parsing A transition-based algorithm for AMR parsing

Reference 63

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.905488Z

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Observation c94483cb-72cf-4fed-bd7a-533ebdb125a4 · outbound

This paper cites AMR -to-text generation with graph transformer.

Evaluation of Finetuned LLMs in AMR Parsing AMR -to-text generation with graph transformer

Reference 64

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.890478Z

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Observation 93149c9b-44ed-4b80-857d-aacc68460e68 · outbound

This paper cites Better amr-to-text generation with graph structure reconstruction.

Evaluation of Finetuned LLMs in AMR Parsing Better amr-to-text generation with graph structure reconstruction

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:41:58.815026Z

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.

Observation 6214a97d-c25c-468a-bcd3-d5967a7efda9 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Evaluation of Finetuned LLMs in AMR Parsing Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T23:41:56.748144Z

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Observation af06a2b8-d2de-45a4-ab79-e663eb5ed29f · outbound

This paper cites Robust Subgraph Generation Improves Abstract Meaning Representation Parsing.

Evaluation of Finetuned LLMs in AMR Parsing Robust Subgraph Generation Improves Abstract Meaning Representation Parsing

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:41:57.523301Z

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

Observation 66ed7532-0caf-450f-b122-be5ac52dcd8c · outbound

This paper cites Intensionalizing A bstract M eaning R epresentations: Non-veridicality and scope.

Evaluation of Finetuned LLMs in AMR Parsing Intensionalizing A bstract M eaning R epresentations: Non-veridicality and scope

Reference 68

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.875138Z

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Observation 1bcd6dde-b055-4d21-88ba-eaa31c0f3b92 · outbound

This paper cites Sentence meaning representations across languages: What can we learn from existing frameworks? Computational Linguistics, 46 0 (3): 0 605--665, September 2020.

Evaluation of Finetuned LLMs in AMR Parsing Sentence meaning representations across languages: What can we learn from existing frameworks? Computational Linguistics, 46 0 (3): 0 605--665, September 2020

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T23:41:56.760588Z

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Unavailable: canonical work link unavailable.

Observation ad8df13b-0d83-48fc-b24b-2334d890b181 · outbound

This paper cites AMR parsing as sequence-to-graph transduction.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing as sequence-to-graph transduction

Reference 70

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.851240Z

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.

Observation c2ffc253-e255-432d-baa4-e4ad639dbb0b · outbound

This paper cites Fine-grained information extraction from biomedical literature based on knowledge-enriched A bstract M eaning R epresentation.

Evaluation of Finetuned LLMs in AMR Parsing Fine-grained information extraction from biomedical literature based on knowledge-enriched A bstract M eaning R epresentation

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T23:41:56.768565Z

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Unavailable: canonical work link unavailable.

Observation c3d7a8c2-ca0b-4fdc-ba39-3ebe76dd330f · outbound

This paper cites Bridging the structural gap between encoding and decoding for data-to-text generation.

Evaluation of Finetuned LLMs in AMR Parsing Bridging the structural gap between encoding and decoding for data-to-text generation

Reference 72

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.837594Z

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.

Observation 21a253f2-7070-4eb5-9fbb-844742a17766 · outbound

This paper cites AMR parsing with action-pointer transformer.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing with action-pointer transformer

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:41:58.703186Z

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.

Observation cedc4925-328f-4e9f-9dcd-526f1c3f4f54 · outbound

This paper cites AMR parsing with an incremental joint model.

Evaluation of Finetuned LLMs in AMR Parsing AMR parsing with an incremental joint model

Reference 74

Resolution: verified exact; doi, observed 2026-08-05T23:41:56.823482Z

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.

Observation 3b3a9aa2-93e9-474d-b2f3-2e33b4c2ab36 · outbound

This paper cites Enhancing battery SOC estimation with BTGE : A novel synergy of filtering, transformer, and ELM.

Evaluation of Finetuned LLMs in AMR Parsing Enhancing battery SOC estimation with BTGE : A novel synergy of filtering, transformer, and ELM

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:41:58.624382Z

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