Paper Citation Record · LEDGER

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback

As of 11 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 2 inbound Pith citation observations for arXiv:2412.17754.

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

pith.paper-citation-record.v1
2412.17754 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:16:05.083081Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T10:19:07.701197Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T10:22:14.521996Z

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy14
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5749b264-ac25-47ff-bcab-745e4661099c · outbound

This paper cites Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.914564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14c15280-e49e-4f95-a4be-77f22d4dcb12 · outbound

This paper cites ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.920807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a73902d4-3baa-4c93-9a51-c1778b084d35 · outbound

This paper cites Code alpaca: An instruction-following llama model for code generation,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Code alpaca: An instruction-following llama model for code generation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.926388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b549a10d-c855-4b8e-ba10-f8f0a63792a3 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.931708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7459a52-0f74-4bd0-9046-fc68ad9b80ca · outbound

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

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.937572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4dd8f72-1dba-4f57-b57c-56a9e550ef6a · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Magicoder: Empowering Code Generation with OSS-Instruct

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.943611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80b6963d-9018-4db3-91fb-84dd0813fd0b · outbound

This paper cites WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.950116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f99601b4-2826-47c4-a97a-7dc8b92dd2e3 · outbound

This paper cites Efficient and scalable estimation of tool representations in vector space,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Efficient and scalable estimation of tool representations in vector space,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.676953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2853e8e3-ec5f-4e66-8ca1-3938accf80e7 · outbound

This paper cites xLAM: A Family of Large Action Models to Empower AI Agent Systems.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback xLAM: A Family of Large Action Models to Empower AI Agent Systems

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.961665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a41a655-703a-433d-aa60-eaba806a42f6 · outbound

This paper cites Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.966983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5180bf5f-a5b1-47eb-948e-6c65c1d2f8c9 · outbound

This paper cites mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecture.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecture

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.972628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec847506-a1a4-4456-8c93-7fb50c2f3fed · outbound

This paper cites Berkeley function calling leaderboard,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Berkeley function calling leaderboard,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.656066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a33b81ad-24bc-43d9-9865-3e36ff1bcc4c · outbound

This paper cites Meta llama 3,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Meta llama 3,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.632649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f74f3039-dba0-42bc-8f11-1dd49afd9954 · outbound

This paper cites GPT-4 Technical Report.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback GPT-4 Technical Report

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:04.989051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 487121f3-f7fc-4b24-93ad-660ea236169d · outbound

This paper cites Claude.ai onboarding,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Claude.ai onboarding,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.612608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d6d9c213-101a-4c97-91db-4193f0464c51 · outbound

This paper cites Language models are few-shot learners,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Language models are few-shot learners,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:05.000289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 462f0a1d-f390-4045-a70c-1002dc7a5fa2 · outbound

This paper cites Hermes-2-pro-llama-3-8b.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Hermes-2-pro-llama-3-8b

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.580366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 17b77f62-64cb-4ec5-b619-daf0478bc379 · outbound

This paper cites Hermes-2-pro-mistral-7b.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Hermes-2-pro-mistral-7b

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.555973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c7b44599-da79-4e55-b877-21fb042409a4 · outbound

This paper cites Hermes-2-theta-llama-3-8b.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Hermes-2-theta-llama-3-8b

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.527704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a55a6e62-7632-4977-b0c0-4d2f60ceb33b · outbound

This paper cites Functionary-small-v3.1,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Functionary-small-v3.1,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.503406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0b6d6add-d2fa-48fb-a5cb-19f43f8eab20 · outbound

This paper cites Functionary-small-v3.2,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Functionary-small-v3.2,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.481370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fa5f4210-cfe5-4e53-b40d-cc1862500905 · outbound

This paper cites Gorilla openfunctions v2,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Gorilla openfunctions v2,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.461330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a22584b6-2b45-4015-9e28-523f574d8deb · outbound

This paper cites CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:05.055403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8a9170-c054-4fec-9dd7-e550df2c397a · outbound

This paper cites Convolutional neural networks over tree structures for programming language processing,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Convolutional neural networks over tree structures for programming language processing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.442847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f881532a-b911-4a47-a056-0eeaaac08d65 · outbound

This paper cites Aizu online judge,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Aizu online judge,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.424212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 016aaa80-c9a0-4734-aba9-7f4aa9f8e2eb · outbound

This paper cites Atcoder,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Atcoder,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.402645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4c733be4-a88e-40ed-9c07-397c7c538715 · outbound

This paper cites APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:05.077306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 207fbd6c-ec5d-48f3-b8d4-795a6e966fcd · outbound

This paper cites Stabletoolbench: Towards stable large-scale benchmarking on tool learning of large language models,.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Stabletoolbench: Towards stable large-scale benchmarking on tool learning of large language models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:16:05.381028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2aa14f56-b340-4a1a-bb74-29780e5945d1 · outbound

This paper cites Language Models are Few-Shot Learners.

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback Language Models are Few-Shot Learners

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T05:16:05.005918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f09cd863-62d9-4022-83eb-dd1540a218da · inbound

AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation cites this paper.

AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:22:14.523639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5c1fa663-aff3-4c88-87d0-4b51e9ec80e1 · inbound

Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study cites this paper.

Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:38:57.899332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.