Paper Citation Record · LEDGER

Can Large Language Models Understand Intermediate Representations in Compilers?

As of 15 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 3 inbound Pith citation observations for arXiv:2502.06854.

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

pith.paper-citation-record.v1
2502.06854 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:20:19.770423Z

measured 73 of 73 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:07:09.491778Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:36:24.038679Z

Reference resolution

70 of 70 outbound references displayed

verified exact2
verified fuzzy31
unresolved36
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8108cc82-b0b8-444b-9660-20da4ca614ac · outbound

This paper cites write newline.

Can Large Language Models Understand Intermediate Representations in Compilers? write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.567624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bcba10f-77a7-4b6b-950e-c737320e3d24 · outbound

This paper cites Malware detection using assembly code and control flow graph optimization.

Can Large Language Models Understand Intermediate Representations in Compilers? Malware detection using assembly code and control flow graph optimization

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.404667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecb6361b-7948-4466-a71f-af0800f88a0c · outbound

This paper cites Claude 3 model, 2024.

Can Large Language Models Understand Intermediate Representations in Compilers? Claude 3 model, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.396706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 199cdeaa-987a-4f87-b1d2-5e9d1f95fc08 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Intermediate Representations in Compilers? Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-08T20:20:20.388712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 36ea26c1-b79b-40d2-93c3-5a387182db74 · outbound

This paper cites S., and Hoefler, T.

Can Large Language Models Understand Intermediate Representations in Compilers? S., and Hoefler, T

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.380882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1a0a6073-a66d-4442-bb87-dfadb8abecd7 · outbound

This paper cites Translating embeddings for modeling multi-relational data.

Can Large Language Models Understand Intermediate Representations in Compilers? Translating embeddings for modeling multi-relational data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.372851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4ac68b53-bfb4-48e9-b608-448eb97256c3 · outbound

This paper cites Compiler-based graph representations for deep learning models of code.

Can Large Language Models Understand Intermediate Representations in Compilers? Compiler-based graph representations for deep learning models of code

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.364449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9b5e15f-ab1a-4575-9bf3-17a4aeeec9e3 · outbound

This paper cites Language Models are Few-Shot Learners.

Can Large Language Models Understand Intermediate Representations in Compilers? Language Models are Few-Shot Learners

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.589916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8a953b4-1bdd-4292-85be-98701e92aa15 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Can Large Language Models Understand Intermediate Representations in Compilers? Evaluating Large Language Models Trained on Code

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.593128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73a281ae-9dec-4b7d-b371-4c67d95efc38 · outbound

This paper cites Intermediate representation: The increasing significance of intermediate representations in compilers.

Can Large Language Models Understand Intermediate Representations in Compilers? Intermediate representation: The increasing significance of intermediate representations in compilers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.356289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2b12701c-d6b1-4fe6-a0a4-9a65cfe34194 · outbound

This paper cites Graph neural networks for vulnerability detection: A counterfactual explanation.

Can Large Language Models Understand Intermediate Representations in Compilers? Graph neural networks for vulnerability detection: A counterfactual explanation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.348054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6d66ef7b-7f34-4602-8667-38623df03bee · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Intermediate Representations in Compilers? Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-08T20:20:20.339589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4689d18b-0201-4459-9fcd-96aded48049f · outbound

This paper cites FASER: Binary Code Similarity Search through the use of Intermediate Representations.

Can Large Language Models Understand Intermediate Representations in Compilers? FASER: Binary Code Similarity Search through the use of Intermediate Representations

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:20:19.818886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 70d6bcfa-6cff-44e1-9d0c-3a80bc03aafe · outbound

This paper cites V., Ben-Nun, T., Hoefler, T., O’Boyle, M.

Can Large Language Models Understand Intermediate Representations in Compilers? V., Ben-Nun, T., Hoefler, T., O’Boyle, M

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.330867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5d995292-5468-4323-a0a6-0d4995421b58 · outbound

This paper cites Meta Large Language Model Compiler: Foundation Models of Compiler Optimization.

Can Large Language Models Understand Intermediate Representations in Compilers? Meta Large Language Model Compiler: Foundation Models of Compiler Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.610627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ddea3e9-1311-4af6-9eb0-2257c5578ec4 · outbound

This paper cites and Lavie, A.

Can Large Language Models Understand Intermediate Representations in Compilers? and Lavie, A

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.322602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 31390888-2631-4433-9f5d-5e3c7432fc61 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Can Large Language Models Understand Intermediate Representations in Compilers? BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.619432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cad1328-8332-4e6e-92f7-3d54ffb6463c · outbound

This paper cites A framework for cfg-based static program analysis of ada programs.

Can Large Language Models Understand Intermediate Representations in Compilers? A framework for cfg-based static program analysis of ada programs

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.314496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecae328e-78ad-4a80-a725-aa0cf2f49f9e · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

Can Large Language Models Understand Intermediate Representations in Compilers? CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.625022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd181dbb-2414-47c0-8ddc-1cef4108f41c · outbound

This paper cites Cross-language binary-source code matching with intermediate representations.

Can Large Language Models Understand Intermediate Representations in Compilers? Cross-language binary-source code matching with intermediate representations

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.306207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 419df42d-cc85-4888-91b3-561a11d54ea6 · outbound

This paper cites GraphCodeBERT: Pre-training Code Representations with Data Flow.

Can Large Language Models Understand Intermediate Representations in Compilers? GraphCodeBERT: Pre-training Code Representations with Data Flow

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.630930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f88ef711-606b-44dd-b173-7927a2a21e1b · outbound

This paper cites UniXcoder: Unified Cross-Modal Pre-training for Code Representation.

Can Large Language Models Understand Intermediate Representations in Compilers? UniXcoder: Unified Cross-Modal Pre-training for Code Representation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.634118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1b7afc5-adbc-458e-85f9-5b9d7068cd42 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Can Large Language Models Understand Intermediate Representations in Compilers? DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.637161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7073a9eb-a990-46f8-93cf-508832b2c379 · outbound

This paper cites Summarizing source code with heterogeneous syntax graph and dual position.

Can Large Language Models Understand Intermediate Representations in Compilers? Summarizing source code with heterogeneous syntax graph and dual position

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.297812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 869950b5-66f0-483a-ace2-962ebe04b68b · outbound

This paper cites Pre-trained models: Past, present and future.

Can Large Language Models Understand Intermediate Representations in Compilers? Pre-trained models: Past, present and future

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.642801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57e4a7b9-4bdf-4e54-8089-0c3aa3a7ddb9 · outbound

This paper cites Happa: A modular platform for hpc application resilience analysis with llms embedded.

Can Large Language Models Understand Intermediate Representations in Compilers? Happa: A modular platform for hpc application resilience analysis with llms embedded

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.284833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5285527a-cc1f-4901-a6a2-fa3e45ac6cc0 · outbound

This paper cites Investigating resilience of loops in hpc programs: A semantic approach with llms.

Can Large Language Models Understand Intermediate Representations in Compilers? Investigating resilience of loops in hpc programs: A semantic approach with llms

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.276205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecc22b21-625d-4395-8415-160b18983df3 · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Can Large Language Models Understand Intermediate Representations in Compilers? A Survey on Large Language Models for Code Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.651009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32785d00-4684-4a05-b3d8-c8c3d3c30ee1 · outbound

This paper cites and Adve, V.

Can Large Language Models Understand Intermediate Representations in Compilers? and Adve, V

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.268046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6f0a88cc-4138-4819-98df-623479d2fb8b · outbound

This paper cites StarCoder: may the source be with you!.

Can Large Language Models Understand Intermediate Representations in Compilers? StarCoder: may the source be with you!

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.656814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7e1f75c-fa32-4177-91af-6648e00b6a86 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Can Large Language Models Understand Intermediate Representations in Compilers? Rouge: A package for automatic evaluation of summaries

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.659892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f22d21c-b1c2-4883-8b65-10f010ad04f8 · outbound

This paper cites S., Wang, Y., and Zhang, L.

Can Large Language Models Understand Intermediate Representations in Compilers? S., Wang, Y., and Zhang, L

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.254595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e7e2d81a-813c-4f34-8d09-023d4065b040 · outbound

This paper cites Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing.

Can Large Language Models Understand Intermediate Representations in Compilers? Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.665531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 757dd848-9590-4897-8b2a-244897d0d7f7 · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.

Can Large Language Models Understand Intermediate Representations in Compilers? Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.246161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0c00387f-e30a-4d32-86cd-e5b793510b16 · outbound

This paper cites Unveiling code pre-trained models: Investigating syntax and semantics capacities.

Can Large Language Models Understand Intermediate Representations in Compilers? Unveiling code pre-trained models: Investigating syntax and semantics capacities

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.237479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c497660c-871c-4de0-93dd-9351d07a0522 · outbound

This paper cites Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs.

Can Large Language Models Understand Intermediate Representations in Compilers? Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.674435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37f9dd35-1c9f-4f91-bd9d-4ad618bbaa4f · outbound

This paper cites Cross-language binary-source code matching based on rust and intermediate representation, 2023.

Can Large Language Models Understand Intermediate Representations in Compilers? Cross-language binary-source code matching based on rust and intermediate representation, 2023

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.229559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 26a38138-3de9-45a2-92f4-81d82fc79c69 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Intermediate Representations in Compilers? Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-08T20:20:20.221638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7006f03f-fee0-44dc-9dbf-aaa499193041 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Can Large Language Models Understand Intermediate Representations in Compilers? Efficient Estimation of Word Representations in Vector Space

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.682858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41e80a8e-c3a3-4392-b9ca-e3f81cadc592 · outbound

This paper cites Fair: Flow type-aware pre-training of compiler intermediate representations.

Can Large Language Models Understand Intermediate Representations in Compilers? Fair: Flow type-aware pre-training of compiler intermediate representations

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.213571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 990d0133-fc56-49f1-88b6-6db164077a7a · outbound

This paper cites Gpt-4 technical report, 2023.

Can Large Language Models Understand Intermediate Representations in Compilers? Gpt-4 technical report, 2023

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.205197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 706e80fd-a50b-40ed-9c0c-bb3bafda5cb1 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Can Large Language Models Understand Intermediate Representations in Compilers? Bleu: a method for automatic evaluation of machine translation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.691517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47885eac-0286-4889-9744-774552798bf8 · outbound

This paper cites S., O'Brien, J., Cai, C.

Can Large Language Models Understand Intermediate Representations in Compilers? S., O'Brien, J., Cai, C

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.694079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d9fdf1b-312a-4c9f-89fc-9841d71b14d0 · outbound

This paper cites IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators.

Can Large Language Models Understand Intermediate Representations in Compilers? IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.696733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6ec78b1-352e-4992-a91a-39ebce94df71 · outbound

This paper cites How could neural networks understand programs? In International Conference on Machine Learning, pp.\ 8476--8486.

Can Large Language Models Understand Intermediate Representations in Compilers? How could neural networks understand programs? In International Conference on Machine Learning, pp.\ 8476--8486

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.187416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 25fb7108-c2a4-40ef-8926-7a7d48a861a1 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Intermediate Representations in Compilers? Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.702301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b85d57c-d33f-436f-ac27-19dad6c8d658 · outbound

This paper cites Pre-trained models for natural language processing: A survey.

Can Large Language Models Understand Intermediate Representations in Compilers? Pre-trained models for natural language processing: A survey

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.174000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 36468b78-04d5-4479-87a1-875061573c2b · outbound

This paper cites Language models are unsupervised multitask learners.

Can Large Language Models Understand Intermediate Representations in Compilers? Language models are unsupervised multitask learners

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.707587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b3d6113-a9a0-4c61-938c-38fa1f553525 · outbound

This paper cites C., Bahmann, H., and Sj \"a lander, M.

Can Large Language Models Understand Intermediate Representations in Compilers? C., Bahmann, H., and Sj \"a lander, M

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.160866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb89b902-48fa-44d7-8486-54ffb9cbc3c6 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Can Large Language Models Understand Intermediate Representations in Compilers? Code Llama: Open Foundation Models for Code

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.713002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76238da5-1567-4edf-857a-e7b7e24ed653 · outbound

This paper cites Polyhedral optimizations for a data-flow graph language.

Can Large Language Models Understand Intermediate Representations in Compilers? Polyhedral optimizations for a data-flow graph language

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.152675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3bb471ef-9e8d-46aa-9d27-90d3e49b004d · outbound

This paper cites LLM4Decompile: Decompiling Binary Code with Large Language Models.

Can Large Language Models Understand Intermediate Representations in Compilers? LLM4Decompile: Decompiling Binary Code with Large Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.718564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42b59d82-1732-4d33-a38d-18d435fc747d · outbound

This paper cites CodeGemma: Open Code Models Based on Gemma.

Can Large Language Models Understand Intermediate Representations in Compilers? CodeGemma: Open Code Models Based on Gemma

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.721408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c8f301e-7f88-44f9-8f4a-a959646760af · outbound

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

Can Large Language Models Understand Intermediate Representations in Compilers? Gemma 2: Improving Open Language Models at a Practical Size

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.724338Z

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Observation b73788ff-6535-4d75-819c-f110fce2db2b · outbound

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

Can Large Language Models Understand Intermediate Representations in Compilers? LLaMA: Open and Efficient Foundation Language Models

Reference 56

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Observation cf7c82c8-ca10-49c7-8968-40f870315c3c · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Can Large Language Models Understand Intermediate Representations in Compilers? N., Kaiser, ., and Polosukhin, I

Reference 57

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This paper cites S., Upadrasta, R., and Srikant, Y.

Can Large Language Models Understand Intermediate Representations in Compilers? S., Upadrasta, R., and Srikant, Y

Reference 58

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Observation 9af925e9-17c1-4124-a38e-215d6bdc01e6 · outbound

This paper cites Deep learning for code intelligence: Survey, benchmark and toolkit.

Can Large Language Models Understand Intermediate Representations in Compilers? Deep learning for code intelligence: Survey, benchmark and toolkit

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.131531Z

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Observation 87fbbc50-cde1-4cfd-ad91-6ee36a16f8f8 · outbound

This paper cites CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation.

Can Large Language Models Understand Intermediate Representations in Compilers? CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 60

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Can Large Language Models Understand Intermediate Representations in Compilers? CodeT5+: Open Code Large Language Models for Code Understanding and Generation

Reference 61

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Can Large Language Models Understand Intermediate Representations in Compilers? J., Utting, M., and Hayes, I

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.122722Z

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Observation 29d0cd3b-0fca-45b4-9a94-0a95ae2ccff4 · outbound

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Can Large Language Models Understand Intermediate Representations in Compilers? V., Zhou, D., et al

Reference 63

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Observation 0dd0d6fb-add9-4d22-8cf0-368cc246836c · outbound

This paper cites Refining Decompiled C Code with Large Language Models.

Can Large Language Models Understand Intermediate Representations in Compilers? Refining Decompiled C Code with Large Language Models

Reference 64

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This paper cites Can Large Language Models Serve as Evaluators for Code Summarization?.

Can Large Language Models Understand Intermediate Representations in Compilers? Can Large Language Models Serve as Evaluators for Code Summarization?

Reference 65

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Observation 3346cd26-81e3-40a4-8762-90cbb9dd4121 · outbound

This paper cites Codecmr: Cross-modal retrieval for function-level binary source code matching.

Can Large Language Models Understand Intermediate Representations in Compilers? Codecmr: Cross-modal retrieval for function-level binary source code matching

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:20:20.109684Z

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Observation 3134506e-3b38-4080-9bb6-86b0624c0655 · outbound

This paper cites Java code clone detection by exploiting semantic and syntax information from intermediate code-based graph.

Can Large Language Models Understand Intermediate Representations in Compilers? Java code clone detection by exploiting semantic and syntax information from intermediate code-based graph

Reference 67

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Observation 1febbc1f-054d-4d6b-863b-7ea2121720bc · outbound

This paper cites A Survey of Large Language Models.

Can Large Language Models Understand Intermediate Representations in Compilers? A Survey of Large Language Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-08T20:20:19.761960Z

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Observation d23bfd67-2df7-42e8-b643-0e3ed328e8e8 · outbound

This paper cites Codegeex: A pre-trained model for code generation with multilingual benchmarking on humaneval-x.

Can Large Language Models Understand Intermediate Representations in Compilers? Codegeex: A pre-trained model for code generation with multilingual benchmarking on humaneval-x

Reference 69

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Observation c85f85d2-c912-4cbb-ac09-e0070e2196f7 · outbound

This paper cites A method for software vulnerability detection based on improved control flow graph.

Can Large Language Models Understand Intermediate Representations in Compilers? A method for software vulnerability detection based on improved control flow graph

Reference 70

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Observation 315755cf-f14c-4033-88b0-a8a999b102ee · outbound

This paper cites Vulnerability localization based on intermediate code representation and feature fusion.

Can Large Language Models Understand Intermediate Representations in Compilers? Vulnerability localization based on intermediate code representation and feature fusion

Reference 71

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Pith citing papers

Observation a3a90a15-9809-41cc-8e7a-0cad555d4be0 · inbound

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps cites this paper.

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps Can Large Language Models Understand Intermediate Representations in Compilers?

Reference 17

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Observation a9603a17-116a-40f2-9344-7b5009389e0b · inbound

LLM Translation of Compiler Intermediate Representation cites this paper.

LLM Translation of Compiler Intermediate Representation Can Large Language Models Understand Intermediate Representations in Compilers?

Reference 16

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Observation e6929ce7-645b-43ac-93c4-76b2a8f9ec25 · inbound

Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss? cites this paper.

Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss? Can Large Language Models Understand Intermediate Representations in Compilers?

Reference 54

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