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Paper Citation Record · LEDGER

Querying Databases with Function Calling

As of 11 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2502.00032.

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

pith.paper-citation-record.v1
2502.00032 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:25:14.757677Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:55:55.391902Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:43:12.535903Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44c96656-731b-4e6d-aee7-226e0e2cc605 · outbound

This paper cites The shift from models to compound ai systems.

Querying Databases with Function Calling The shift from models to compound ai systems

Reference 1

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no resolver link, observed 2026-08-10T15:25:14.452458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.452458Z digest=sha256:f2028a4fa88aff998f73cf42bacd2b92898263b23ef9b110a03fff4c1b929a9f

Observation f590d163-f1ad-4136-a398-698120eb9532 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Querying Databases with Function Calling ReAct: Synergizing Reasoning and Acting in Language Models

Reference 2

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no resolver link, observed 2026-08-10T15:25:14.457911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.457911Z digest=sha256:9042818f29e665a4e07de8fd9a0cf4c7bc6f7ce1ffb7d43cc30b0c6cb8a8ce59

Observation 2056d2ed-38e9-4762-81e3-ac34772d7c37 · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

Querying Databases with Function Calling Gorilla: Large Language Model Connected with Massive APIs

Reference 3

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no resolver link, observed 2026-08-10T15:25:14.463745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.463745Z digest=sha256:1b3550621a7e9c422ef5a7a0392db9c781765b0a9692409f61bf9e1b0409d783

Observation 7be744dc-215e-415a-9d39-0ef2e0ec80bc · outbound

This paper cites Function calling in the chat completions api.

Querying Databases with Function Calling Function calling in the chat completions api

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.479712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.468659Z digest=sha256:3bf05f42d41d93abc1d240570d07426a96c6c088a276dfd6762dd99f94efeed9

Observation a82266f5-4043-40a6-b40d-f2ad9964ea33 · outbound

This paper cites Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows.

Querying Databases with Function Calling Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Reference 5

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no resolver link, observed 2026-08-10T15:25:14.473377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.473377Z digest=sha256:da4789184e1d2a3e60adf2ed864f0acea47fcfdcdc8bc67f0c2f200d36d9c736

Observation 307fdf2f-0cb9-4852-ad59-101c7128a9b5 · outbound

This paper cites STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases.

Querying Databases with Function Calling STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases

Reference 6

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no resolver link, observed 2026-08-10T15:25:14.478426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.478426Z digest=sha256:5debf30ef555daa3d3675a8dfdc0e7aee57347faeb1d68493367564de80f54be

Observation f7df761c-30c1-4bf4-9191-404dffa8aaf5 · outbound

This paper cites https://www.w3.org/TR/sparql11-query/, 2013.

Querying Databases with Function Calling https://www.w3.org/TR/sparql11-query/, 2013

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.465430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.483725Z digest=sha256:4cd24900db9f2f847cb9a9eb21837998255805388a5132378c60a752a17c6b46

Observation e6516d01-c63b-4de7-b0ca-6b60d6b458da · outbound

This paper cites Semantic Operators: A Declarative Model for Rich, AI-based Data Processing.

Querying Databases with Function Calling Semantic Operators: A Declarative Model for Rich, AI-based Data Processing

Reference 8

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no resolver link, observed 2026-08-10T15:25:14.487966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.487966Z digest=sha256:d9597230a4bc0fc58db4f31d61056f80b114f19ca440636da619dda84e2aa9dd

Observation 4c166f4d-a604-4454-92de-549f28418658 · outbound

This paper cites Text2SQL is Not Enough: Unifying AI and Databases with TAG.

Querying Databases with Function Calling Text2SQL is Not Enough: Unifying AI and Databases with TAG

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T15:25:14.492794Z digest=sha256:45d1fb4ec109d6a139e5ea87cdba07d2eee1057e60f856da515955c7bcafa2a9

Observation 119a3000-24a5-4a6a-a4b0-51776d4343b9 · outbound

This paper cites SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models.

Querying Databases with Function Calling SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models

Reference 10

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no resolver link, observed 2026-08-10T15:25:14.497542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.497542Z digest=sha256:c3d59b976fdbe90194892bf088054b9152fbc64f8cacf7d22a6fdbfff2fc209c

Observation 90315ad8-2f76-4631-b290-119bfdfb1c77 · outbound

This paper cites Patil, Ion Stoica, and Joseph E.

Querying Databases with Function Calling Patil, Ion Stoica, and Joseph E

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.450362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.502397Z digest=sha256:339d320ab03a969cfc5710ef453881a41f1030f5bd4d317846def1de1d26a11d

Observation 4c95fb91-76e4-4e3e-96c4-34cc4f201cf9 · outbound

This paper cites Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering.

Querying Databases with Function Calling Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.506508Z digest=sha256:cc96d969f88a5e46c5749a39bb17b558586c842cec20596fea6e74f8d8468306

Observation afb9f218-ef9f-4753-9f35-d68aff4109ea · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Querying Databases with Function Calling Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.436317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.510726Z digest=sha256:449b35effb67eda03503722aeb265430adbb5ccd9c13a0402df179ce95692ea1

Observation 1167535b-c7f3-411f-9a76-4e17502fe2c1 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Querying Databases with Function Calling WebGPT: Browser-assisted question-answering with human feedback

Reference 14

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no resolver link, observed 2026-08-10T15:25:14.514772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.514772Z digest=sha256:cef8441b8779e4597bb30f706a81b40505ea7519847711f6f7c5b2f4af0fcf84

Observation 7fdda458-1e01-4e4b-9282-f142523cf068 · outbound

This paper cites Agentic Information Retrieval.

Querying Databases with Function Calling Agentic Information Retrieval

Reference 15

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no resolver link, observed 2026-08-10T15:25:14.519161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.519161Z digest=sha256:9870acbc67e67c94b96f9aaed88d95f2f8a77aa38f8616629371b64265e9747c

Observation b4ea0825-994d-41a7-97d7-1d8f2b45dcb6 · outbound

This paper cites Next- generation database interfaces: A survey of llm-based text-to-sql.

Querying Databases with Function Calling Next- generation database interfaces: A survey of llm-based text-to-sql

Reference 16

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no resolver link, observed 2026-08-10T15:25:14.523602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.523602Z digest=sha256:51542d9ff532d46d88f7027914e85d3c171c5cbf6176244ee9244f8541b4a468

Observation dd34f70d-5c6d-4220-9177-89ee85fd8894 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

Querying Databases with Function Calling Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 17

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no resolver link, observed 2026-08-10T15:25:14.528460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.528460Z digest=sha256:271930d577eec803e6a038383632e6d5335da13a5d64339002d5cad26f4655d9

Observation 8d8e131f-81f9-492d-94c7-b7b090f1db5a · outbound

This paper cites Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task.

Querying Databases with Function Calling Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.422204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.533110Z digest=sha256:d38a811602a44bd3f9569e1c66cad464358368e75aef160a88032fcb4b3ae3cc

Observation 9569ba60-5efe-4bd4-a8dc-fe5169bffe0c · outbound

This paper cites Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.

Querying Databases with Function Calling Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.407945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.640045Z digest=sha256:b6fcaa5ff2999a91609f5c4dfdc2d66fc2f213d76e199bf373e3e0c2c48a5da5

Observation c018154d-1eea-445e-a148-76902e397de0 · outbound

This paper cites Lakehouse: A new generation of open platforms that unify data warehousing and advanced analytics.

Querying Databases with Function Calling Lakehouse: A new generation of open platforms that unify data warehousing and advanced analytics

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.393977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.644951Z digest=sha256:e3445e7e5c48a9cd5e7f582f77738fd3826c42acb2d2f77e07f9e747c5b2bfc1

Observation ce859429-e5ba-457f-a9a8-6b9c27db1ef2 · outbound

This paper cites Bringing semantic knowledge graph technology to your data.

Querying Databases with Function Calling Bringing semantic knowledge graph technology to your data

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.379001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.649659Z digest=sha256:9bc99319e72b6ae46fc807dbb87b2334131ba44252a1439b8f3b282c2327aa4c

Observation bfb9049a-06b9-4e22-bea1-e4acede9bc4c · outbound

This paper cites Database gyms.

Querying Databases with Function Calling Database gyms

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.362602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.654109Z digest=sha256:e0a2131cc5b8d0557dd99f30a8a0524a71581cb39ce40360895860465e009bcb

Observation 994f3986-3752-4ccd-8639-dd0b8bc48d52 · outbound

This paper cites GPT-4 Technical Report.

Querying Databases with Function Calling GPT-4 Technical Report

Reference 23

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no resolver link, observed 2026-08-10T15:25:14.658982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.658982Z digest=sha256:908663e58085e0d288b53dee44f8a10096e6e6d051260aa1227887fd29daa28f

Observation a0578653-36cc-46bf-8e1f-25ff5e4e5a33 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Querying Databases with Function Calling Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 24

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no resolver link, observed 2026-08-10T15:25:14.663456Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T15:25:14.663456Z digest=sha256:0259756f6315826b4ffa9a7994065d74a4a8d75ac098ebbcd5673df4d947f2af

Observation f7e6ecb9-246f-4ea2-b81a-4f3a0cf12e01 · outbound

This paper cites https://www.anthropic.com/news/claude-3-5-sonnet , 2024.

Querying Databases with Function Calling https://www.anthropic.com/news/claude-3-5-sonnet , 2024

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.346766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.668245Z digest=sha256:063d1eda1a3b75eb05070dbdd23a3ec30e133a5bc20aafd4ce00c31f64f74f0a

Observation 672c60aa-cc74-4c96-8bdd-e02b8c8865a6 · outbound

This paper cites https://docs.cohere.com/v2/docs/command-r, 2024.

Querying Databases with Function Calling https://docs.cohere.com/v2/docs/command-r, 2024

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.331110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.672771Z digest=sha256:bddf25caac700ea7b79c0d98d6fe36f53b0845b6f80a7b02bf12982aa95c9970

Observation cecc3624-88aa-45c0-a4d4-c62e0dc8e317 · outbound

This paper cites Llama 3 model card, Accessed July 2024.

Querying Databases with Function Calling Llama 3 model card, Accessed July 2024

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.315897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.677474Z digest=sha256:c2a3fc97dbbff197d8114faaf8cecb5927d0164119ebe7153aaafa78839e5154

Observation bb433a3e-b17f-4e52-be3a-f2a778057cc2 · outbound

This paper cites Efficient Guided Generation for Large Language Models.

Querying Databases with Function Calling Efficient Guided Generation for Large Language Models

Reference 28

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no resolver link, observed 2026-08-10T15:25:14.682131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.682131Z digest=sha256:69178a00906fd1f55018499e8196862b37c8fdb0006e967d887f2153f783b23f

Observation cf58936a-788a-484a-a9a5-2ddcad04c274 · outbound

This paper cites Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models.

Querying Databases with Function Calling Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models

Reference 29

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no resolver link, observed 2026-08-10T15:25:14.687203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.687203Z digest=sha256:4f6da60325a1225a68bac0fa48aba978b829ff55621de508107d1098e6770966

Observation 832fda25-a923-42f2-ac78-64a05f15037b · outbound

This paper cites StructuredRAG: JSON Response Formatting with Large Language Models.

Querying Databases with Function Calling StructuredRAG: JSON Response Formatting with Large Language Models

Reference 30

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no resolver link, observed 2026-08-10T15:25:14.691850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.691850Z digest=sha256:61d0d76b5fcfdfa661424d3556b833a397c2cf37b1a62f3df7886a1f36ec3e97

Observation 191fe18a-dfa9-4998-bc4a-96b9e9e9d33d · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

Querying Databases with Function Calling Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:25:15.300193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:25:14.696630Z digest=sha256:419c63a4de6e0141c847734eb49462f510d3c3c3edae071d7197e7f66f45d4a6

Observation de9c5c3d-19e4-4fb9-ba76-2e793f7c0b5c · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Querying Databases with Function Calling Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-10T15:25:14.705494Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T15:25:14.705494Z digest=sha256:1e5a2ca9a61b727b5d786e2bdc5b0ddc58965f58fdaa2b894cb171ab7e2920d0

Observation b53a0fad-e239-4c54-9542-0bb59eee9494 · outbound

This paper cites DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines.

Querying Databases with Function Calling DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines

Reference 34

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no resolver link, observed 2026-08-10T15:25:14.709782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.709782Z digest=sha256:a3899370c8dee2366e41b42c8542e3bb46a3a36f922d075c4409102c85598333

Observation e54f6caf-209e-446d-a31d-7ce2f8a703bb · outbound

This paper cites SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelines.

Querying Databases with Function Calling SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelines

Reference 35

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no resolver link, observed 2026-08-10T15:25:14.714751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.714751Z digest=sha256:2e544179e19f4f8ad77d1ce3a45b62f84820b0a98e7633b35f3db706b4381f4e

Observation 0a22cc6d-1acf-494b-8fab-6077c4890e1b · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Querying Databases with Function Calling Direct preference optimization: Your language model is secretly a reward model

Reference 36

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no resolver link, observed 2026-08-10T15:25:14.719672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.719672Z digest=sha256:0c316192a8f4784f93cf6012a879c44f3cc80a2c69f302ace0a13abc767661ec

Observation d99aa396-35b2-4af2-85cb-93987f5637f6 · outbound

This paper cites Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment.

Querying Databases with Function Calling Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment

Reference 37

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no resolver link, observed 2026-08-10T15:25:14.724337Z

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source=pdf_text observed=2026-08-10T15:25:14.724337Z digest=sha256:344f1c30a4e7b11df6fbda9d383a111735542dd42b37404ad0c167bc55d9e41e

Observation 7f0810ce-9013-43af-89ea-c076673a2409 · outbound

This paper cites GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications.

Querying Databases with Function Calling GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications

Reference 38

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no resolver link, observed 2026-08-10T15:25:14.729494Z

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source=pdf_text observed=2026-08-10T15:25:14.729494Z digest=sha256:848d267f705326787a5ee9fcd54b98990367cae5a63580b092b60f1e90c2a177

Observation 549341de-d95d-4e83-a469-8592eeb0cccc · outbound

This paper cites Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design.

Querying Databases with Function Calling Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design

Reference 39

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source=pdf_text observed=2026-08-10T15:25:14.734364Z digest=sha256:da9f1e0950d36bd6ddeec8b98ff835c38d640579d4643ee141390449d2827078

Observation be38f18a-8efd-4c1e-80e5-e02ddecde328 · outbound

This paper cites Specifications: The missing link to making the development of LLM systems an engineering discipline.

Querying Databases with Function Calling Specifications: The missing link to making the development of LLM systems an engineering discipline

Reference 40

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no resolver link, observed 2026-08-10T15:25:14.738844Z

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source=pdf_text observed=2026-08-10T15:25:14.738844Z digest=sha256:2c95a54a2596e05bc5fe7ab2700fce63b992eb74592007e3f1fd126ccdc59a53

Observation c4aebb85-5254-4264-b921-81fce4b48be3 · outbound

This paper cites Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP.

Querying Databases with Function Calling Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Reference 41

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no resolver link, observed 2026-08-10T15:25:14.743431Z

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source=pdf_text observed=2026-08-10T15:25:14.743431Z digest=sha256:b510e86090456351fed43ce65e6433c7a8045d230b36ff1b181e630f3d5a661b

Observation 11c17fca-f40f-45b4-b514-83287f97f17e · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

Querying Databases with Function Calling DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 42

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source=pdf_text observed=2026-08-10T15:25:14.747597Z digest=sha256:025370aef3537d28a613d0929f838e4c22851af6cea6f561eab399a2ecc2a059

Observation 07fb4be5-6b6e-4915-87ed-7552e02ba394 · outbound

This paper cites Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs.

Querying Databases with Function Calling Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 43

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no resolver link, observed 2026-08-10T15:25:14.752902Z

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source=pdf_text observed=2026-08-10T15:25:14.752902Z digest=sha256:f87b50783acf0f5aeaa8c23c7a4c5bbdb877cb35e12d9cd6fd251e9f5d5d2a18

Observation 4fb2c28e-9508-45d7-8250-034b958a2d60 · outbound

This paper cites AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning.

Querying Databases with Function Calling AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning

Reference 44

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source=pdf_text observed=2026-08-10T15:25:14.757677Z digest=sha256:48710969d9938a04fae78d77f636e8e7d2f208d416a0dd1ff72516d677e6c91e

Pith citing papers

Observation 1e4a7548-fd0a-4566-a3b4-fe36d27df615 · inbound

AgentNLQ: A General-Purpose Agent for Natural Language to SQL cites this paper.

AgentNLQ: A General-Purpose Agent for Natural Language to SQL Querying Databases with Function Calling

Reference 10

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verified exact
arxiv_id, observed 2026-05-20T10:43:12.537353Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T10:41:17.671666Z digest=sha256:2410554aeaa33325434c6a92760a823b75489e287260a41dc4bbdc1bdf8243ec

Observation a11e1efb-932a-4bf4-bf78-40abb888a892 · inbound

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems cites this paper.

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems Querying Databases with Function Calling

Reference 107

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source=pdf_text observed=2026-08-03T00:55:55.391902Z digest=sha256:2a0657b3b9ba33693fb7f25b012ab7023cf70998ce61ae1868bfd8ed83aa9c57