Paper Citation Record · LEDGER

Improving Large Language Models with Concept-Aware Fine-Tuning

As of 19 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 2 inbound Pith citation observations for arXiv:2506.07833.

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

pith.paper-citation-record.v1
2506.07833 v2

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:28:23.993007Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:48:51.218298Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

63 of 63 outbound references displayed

verified exact2
verified fuzzy34
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 12561326-0cdf-431d-b61e-676f88fec198 · outbound

This paper cites A dataset and benchmark for hospital course summarization with adapted large language models // Journal of the American Medical Informatics Association.

Improving Large Language Models with Concept-Aware Fine-Tuning A dataset and benchmark for hospital course summarization with adapted large language models // Journal of the American Medical Informatics Association

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.638398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2e509308-4d88-4def-82c6-2044a8741aed · outbound

This paper cites Program Synthesis with Large Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning Program Synthesis with Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.803956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bb6ceb4-7e4c-48e3-9b5c-12a1b4ca336c · outbound

This paper cites The pitfalls of next-token prediction.

Improving Large Language Models with Concept-Aware Fine-Tuning The pitfalls of next-token prediction

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.808234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5e4d91c-382e-4730-9b7d-304e832701c4 · outbound

This paper cites Large Concept Models: Language Modeling in a Sentence Representation Space.

Improving Large Language Models with Concept-Aware Fine-Tuning Large Concept Models: Language Modeling in a Sentence Representation Space

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.811740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f54c252-cd71-4bf5-9b1c-21a3f18d2952 · outbound

This paper cites Language models are few-shot learners // Advances in neural information processing systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Language models are few-shot learners // Advances in neural information processing systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.629858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d98e0efc-fb5f-45e0-a1ac-e19d643a7ef1 · outbound

This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Improving Large Language Models with Concept-Aware Fine-Tuning Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.818196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c3af472-0ab6-4a1c-8c78-f7698a88b29e · outbound

This paper cites Code Alpaca: An Instruction-following LLaMA model for code generation.

Improving Large Language Models with Concept-Aware Fine-Tuning Code Alpaca: An Instruction-following LLaMA model for code generation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.621486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 95597ad8-9af0-4e64-bf5c-9a0ac1b6edad · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Improving Large Language Models with Concept-Aware Fine-Tuning Evaluating Large Language Models Trained on Code

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.824947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d8e7afd-0c1b-42ec-ad31-7d2a76d554fc · outbound

This paper cites JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.828084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e01e88be-cb18-44f6-acb1-bbf9388ab8fd · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Improving Large Language Models with Concept-Aware Fine-Tuning Training Verifiers to Solve Math Word Problems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.831576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc39df4-742d-4c36-9534-98762cdf700d · outbound

This paper cites Qlora: Efficient finetuning of quantized llms // Advances in neural information processing systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Qlora: Efficient finetuning of quantized llms // Advances in neural information processing systems

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.614002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 810448c8-774f-45db-b0b6-2fef15a9bd89 · outbound

This paper cites an unresolved cited work.

Improving Large Language Models with Concept-Aware Fine-Tuning Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:28:24.605669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d03d0764-a594-41c4-9010-28e2f145fdb0 · outbound

This paper cites Faith and fate: Limits of transformers on compositionality // Advances in Neural Information Processing Systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Faith and fate: Limits of transformers on compositionality // Advances in Neural Information Processing Systems

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.597930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48a57128-16aa-4d84-8b01-12a3247ef01f · outbound

This paper cites L+M-24: Building a Dataset for Language + Molecules @ ACL 2024.

Improving Large Language Models with Concept-Aware Fine-Tuning L+M-24: Building a Dataset for Language + Molecules @ ACL 2024

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:28:24.304529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3aac82e0-b5f5-4dae-ac7a-0f0f676c0d49 · outbound

This paper cites Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.847016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b3fcfab-0b43-4181-83bd-9a7d94dcaf30 · outbound

This paper cites Bridging the data gap between children and large language models // Trends in Cognitive Sciences.

Improving Large Language Models with Concept-Aware Fine-Tuning Bridging the data gap between children and large language models // Trends in Cognitive Sciences

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.588568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a2ec83bb-6e7c-4cd3-b8ec-5fa6b607a700 · outbound

This paper cites Better & Faster Large Language Models via Multi-token Prediction.

Improving Large Language Models with Concept-Aware Fine-Tuning Better & Faster Large Language Models via Multi-token Prediction

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.853884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b14736c-197a-4e1b-8386-6d34f635b68d · outbound

This paper cites Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance.

Improving Large Language Models with Concept-Aware Fine-Tuning Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.856911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46b7bc9e-1fc9-4998-9824-9ed03e7ec06e · outbound

This paper cites The Llama 3 Herd of Models.

Improving Large Language Models with Concept-Aware Fine-Tuning The Llama 3 Herd of Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.860206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54344d67-9455-4cde-b527-59167f4d67b9 · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space.

Improving Large Language Models with Concept-Aware Fine-Tuning Training Large Language Models to Reason in a Continuous Latent Space

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.862979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb01dbcc-54cc-49b6-9794-a36e472f14ba · outbound

This paper cites Amino acid substitution matrices from protein blocks.

Improving Large Language Models with Concept-Aware Fine-Tuning Amino acid substitution matrices from protein blocks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.580485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9c6c07c1-31a9-43c9-8ac1-b479c4a820cc · outbound

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

Improving Large Language Models with Concept-Aware Fine-Tuning Lora: Low-rank adaptation of large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.572625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d06001be-5d2d-42d2-b35c-3610d3db8d73 · outbound

This paper cites MIMIC-IV, a freely accessible electronic health record dataset // Scientific data.

Improving Large Language Models with Concept-Aware Fine-Tuning MIMIC-IV, a freely accessible electronic health record dataset // Scientific data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.565075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 33605d40-1617-436a-a068-1db1fd2ec00c · outbound

This paper cites Highly accurate protein structure prediction with AlphaFold // nature.

Improving Large Language Models with Concept-Aware Fine-Tuning Highly accurate protein structure prediction with AlphaFold // nature

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.557082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0ccf116c-f6be-47a5-bfc4-12f83c2af567 · outbound

This paper cites Concept bottleneck models // International conference on machine learning.

Improving Large Language Models with Concept-Aware Fine-Tuning Concept bottleneck models // International conference on machine learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.549762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fb45db1c-1a6e-4d29-9076-06a4175826fa · outbound

This paper cites De novo protein design—From new structures to programmable functions // Cell.

Improving Large Language Models with Concept-Aware Fine-Tuning De novo protein design—From new structures to programmable functions // Cell

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.541629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b220b0a3-5a00-4cb2-a857-7b450ecd4710 · outbound

This paper cites Attribute and simile classifiers for face verification // 2009 IEEE 12th international conference on computer vision.

Improving Large Language Models with Concept-Aware Fine-Tuning Attribute and simile classifiers for face verification // 2009 IEEE 12th international conference on computer vision

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.533481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7d58bae-cd38-473b-a1a0-93c34149fbd0 · outbound

This paper cites Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:28:24.260138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ff18b06-e29f-4b0b-afcf-349bc3cad08b · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Improving Large Language Models with Concept-Aware Fine-Tuning Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.889757Z

Source-reported events for the cited work

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Observation 57556b8b-1303-4685-b8b3-88840a7c24d0 · outbound

This paper cites Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions // Hugging Face repository.

Improving Large Language Models with Concept-Aware Fine-Tuning Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions // Hugging Face repository

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.525278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5c12e27-8930-47c2-9e25-75c49badcd49 · outbound

This paper cites Pre-trained language models for text generation: A survey // ACM Computing Surveys.

Improving Large Language Models with Concept-Aware Fine-Tuning Pre-trained language models for text generation: A survey // ACM Computing Surveys

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.516936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4acc6a26-db0c-4dbb-a05c-7b2ade845432 · outbound

This paper cites Table-GPT: Table-tuned GPT for Diverse Table Tasks.

Improving Large Language Models with Concept-Aware Fine-Tuning Table-GPT: Table-tuned GPT for Diverse Table Tasks

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.899093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bddd19e-cb96-4f12-9864-0fe9f2de6e5c · outbound

This paper cites Let's verify step by step // The Twelfth International Conference on Learning Representations.

Improving Large Language Models with Concept-Aware Fine-Tuning Let's verify step by step // The Twelfth International Conference on Learning Representations

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.509070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e67d8cf-1143-491f-b98c-b7d200f93880 · outbound

This paper cites an unresolved cited work.

Improving Large Language Models with Concept-Aware Fine-Tuning Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:28:24.501465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3a5d22d4-a9d6-45c7-b9a3-31492d550b35 · outbound

This paper cites Ben, Zimmerman Sam, Rivoire Kelley, Conerly Thomas, Olah Chris, Batson Joshua.

Improving Large Language Models with Concept-Aware Fine-Tuning Ben, Zimmerman Sam, Rivoire Kelley, Conerly Thomas, Olah Chris, Batson Joshua

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.493837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba30d372-02d6-4d85-8a3c-b23fa7c9cf54 · outbound

This paper cites DeepSeek-V3 Technical Report.

Improving Large Language Models with Concept-Aware Fine-Tuning DeepSeek-V3 Technical Report

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.912496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7961aade-6835-4bc4-9b9d-822bfa6e7d89 · outbound

This paper cites SuperBPE: Space Travel for Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning SuperBPE: Space Travel for Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.915536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30b95365-5af2-40c3-b92b-c5556d29a205 · outbound

This paper cites AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling.

Improving Large Language Models with Concept-Aware Fine-Tuning AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.918291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d22a078-2413-41ea-a72a-d57144ee9889 · outbound

This paper cites The flan collection: Designing data and methods for effective instruction tuning // International Conference on Machine Learning.

Improving Large Language Models with Concept-Aware Fine-Tuning The flan collection: Designing data and methods for effective instruction tuning // International Conference on Machine Learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.485923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 91ac9bee-9584-4856-ad42-c8805314820f · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

Improving Large Language Models with Concept-Aware Fine-Tuning WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.478303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2cb5da11-23d5-41e0-9628-7d753a9a623c · outbound

This paper cites De novo molecular design and generative models // Drug discovery today.

Improving Large Language Models with Concept-Aware Fine-Tuning De novo molecular design and generative models // Drug discovery today

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.471051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 58843eac-80f5-49fe-9198-09608ee574cc · outbound

This paper cites Levenshtein distance: Information theory, computer science, string (computer science), string metric, damerau? Levenshtein distance, spell checker, hamming distance.

Improving Large Language Models with Concept-Aware Fine-Tuning Levenshtein distance: Information theory, computer science, string (computer science), string metric, damerau? Levenshtein distance, spell checker, hamming distance

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.463328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e923f9a5-1a4b-4ddc-8873-3ba5f8316e3f · outbound

This paper cites ColabFold: making protein folding accessible to all // Nature methods.

Improving Large Language Models with Concept-Aware Fine-Tuning ColabFold: making protein folding accessible to all // Nature methods

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.456118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b1f27967-4015-45cc-b342-e5e1036f6186 · outbound

This paper cites A general method applicable to the search for similarities in the amino acid sequence of two proteins // Journal of molecular biology.

Improving Large Language Models with Concept-Aware Fine-Tuning A general method applicable to the search for similarities in the amino acid sequence of two proteins // Journal of molecular biology

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.448351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a688db36-6b30-45e1-9ddf-780c162b8007 · outbound

This paper cites Training language models to follow instructions with human feedback // Advances in neural information processing systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Training language models to follow instructions with human feedback // Advances in neural information processing systems

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.441391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f6751e21-240e-48bc-972c-a31ea6e0162e · outbound

This paper cites Improving language understanding by generative pre-training.(2018).

Improving Large Language Models with Concept-Aware Fine-Tuning Improving language understanding by generative pre-training.(2018)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.433463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8d9c750-7432-4b1f-b6f0-feebbe8a93e3 · outbound

This paper cites Twilight zone of protein sequence alignments // Protein engineering.

Improving Large Language Models with Concept-Aware Fine-Tuning Twilight zone of protein sequence alignments // Protein engineering

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.425033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d71c7a00-7ef5-4bf4-bdc2-60f1526f3e4a · outbound

This paper cites Get Your Atoms in Order: An Open-Source Implementation of a Novel and Robust Molecular Canonicalization Algorithm // Journal of chemical information and modeling.

Improving Large Language Models with Concept-Aware Fine-Tuning Get Your Atoms in Order: An Open-Source Implementation of a Novel and Robust Molecular Canonicalization Algorithm // Journal of chemical information and modeling

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.416899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07928385-739e-4eff-8c82-72f6a5d54992 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Improving Large Language Models with Concept-Aware Fine-Tuning Neural Machine Translation of Rare Words with Subword Units

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.950123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c1425b3-a0ea-4650-87da-03f84fd969ff · outbound

This paper cites A mathematical theory of communication // The Bell system technical journal.

Improving Large Language Models with Concept-Aware Fine-Tuning A mathematical theory of communication // The Bell system technical journal

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.408503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 260d899d-5546-4b5b-9352-9fc8864fd913 · outbound

This paper cites Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs.

Improving Large Language Models with Concept-Aware Fine-Tuning Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.956370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2068eae3-0832-459d-8509-9a1cdad9c3d3 · outbound

This paper cites Blockwise parallel decoding for deep autoregressive models // Advances in Neural Information Processing Systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Blockwise parallel decoding for deep autoregressive models // Advances in Neural Information Processing Systems

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.399779Z

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Observation 9393101f-8d37-4692-8299-ce5998ef4b9e · outbound

This paper cites Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies.

Improving Large Language Models with Concept-Aware Fine-Tuning Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.962571Z

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Observation 8393c317-7ac5-4d48-9760-cee7642c1ecd · outbound

This paper cites OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data.

Improving Large Language Models with Concept-Aware Fine-Tuning OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.965512Z

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Observation 4b6d841d-186f-4680-8dff-abc097a4c8c7 · outbound

This paper cites Attention is all you need // Advances in neural information processing systems.

Improving Large Language Models with Concept-Aware Fine-Tuning Attention is all you need // Advances in neural information processing systems

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.391096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5395233b-013c-442a-9754-809b735b346c · outbound

This paper cites Sciriff: A resource to enhance language model instruction-following over scientific literature // arXiv preprint arXiv:2406.07835.

Improving Large Language Models with Concept-Aware Fine-Tuning Sciriff: A resource to enhance language model instruction-following over scientific literature // arXiv preprint arXiv:2406.07835

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.970765Z

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Observation 4b334a26-05c3-4280-9e93-106571b0c114 · outbound

This paper cites Transformers: State-of-the-art natural language processing // Proceedings of the 2020 conference on empirical methods in natural language processing: system demonstrations.

Improving Large Language Models with Concept-Aware Fine-Tuning Transformers: State-of-the-art natural language processing // Proceedings of the 2020 conference on empirical methods in natural language processing: system demonstrations

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.383404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 06a09b59-b44d-4459-8ab6-d8c233df379f · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions // The Twelfth International Conference on Learning Representations.

Improving Large Language Models with Concept-Aware Fine-Tuning WizardLM: Empowering large pre-trained language models to follow complex instructions // The Twelfth International Conference on Learning Representations

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.375507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32334a21-c525-4fb1-ba2d-079f7117e89d · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Improving Large Language Models with Concept-Aware Fine-Tuning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.979753Z

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Observation 701a2e50-71c7-4c70-96d5-67a2ff2e39fd · outbound

This paper cites Scoring function for automated assessment of protein structure template quality // Proteins: Structure, Function, and Bioinformatics.

Improving Large Language Models with Concept-Aware Fine-Tuning Scoring function for automated assessment of protein structure template quality // Proteins: Structure, Function, and Bioinformatics

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.366097Z

Source-reported events for the cited work

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Observation fe723ed0-ed49-458e-aa61-deba29655f78 · outbound

This paper cites Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space.

Improving Large Language Models with Concept-Aware Fine-Tuning Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.986449Z

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Observation 11839ef5-e3bd-4061-84c5-acadd2c53706 · outbound

This paper cites WildChat: 1M ChatGPT Interaction Logs in the Wild.

Improving Large Language Models with Concept-Aware Fine-Tuning WildChat: 1M ChatGPT Interaction Logs in the Wild

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:23.989799Z

Source-reported events for the cited work

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Observation 7299156b-02c5-4ea9-8cc0-da7200d721c9 · outbound

This paper cites P, Zhang Hao, Gonzalez Joseph E., Stoica Ion.

Improving Large Language Models with Concept-Aware Fine-Tuning P, Zhang Hao, Gonzalez Joseph E., Stoica Ion

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:28:24.357953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 18e95850-7f60-4ca1-be1e-affab7bc3de7 · inbound

From Found to Designed: Concepts as a Design Axis for Large Language Models cites this paper.

From Found to Designed: Concepts as a Design Axis for Large Language Models Improving Large Language Models with Concept-Aware Fine-Tuning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-30T19:59:23.665213Z

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Observation 4a404dbe-02ea-447c-9fab-c2d34e51bf7c · inbound

From Found to Designed: Concepts as a Design Axis for Large Language Models cites this paper.

From Found to Designed: Concepts as a Design Axis for Large Language Models Improving Large Language Models with Concept-Aware Fine-Tuning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T10:48:51.218298Z

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