Pith. sign in

Paper Citation Record · LEDGER

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering

As of 15 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2507.03018.

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

pith.paper-citation-record.v1
2507.03018 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:48:15.795768Z

measured 19 of 19 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9655f6b-a721-461a-b922-e5feb34f39a9 · outbound

This paper cites The Llama 3 Herd of Models.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering The Llama 3 Herd of Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.439919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.439919Z digest=sha256:f521f1446a8d57782d8c633a5f1b87580213b8a28dd51d762e37d474096230ab

Observation 48ba2f14-1ff3-431c-bf7e-27661b8a3de8 · outbound

This paper cites Qwen2.5 technical report, 2025.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Qwen2.5 technical report, 2025

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.506241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.506241Z digest=sha256:fa99e8315d6f4ac4638a95ece9366b0e89b22744bbb5a901a4902a5999dbaf96

Observation eaaa8038-770b-4763-bf7e-28247a1cf1c1 · outbound

This paper cites Qwen3 Technical Report.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Qwen3 Technical Report

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.565267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.565267Z digest=sha256:70a7aa2e2aa64afd9e9eb2690a18e56f875f87b0f291dcbed7da5f58a0934acf

Observation 71dbe344-1917-4f2c-9978-99864768be26 · outbound

This paper cites Proximal Policy Optimization Algorithms.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Proximal Policy Optimization Algorithms

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.611393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.611393Z digest=sha256:626276af8c4480bfcd8a1b3bfcc0d7cd3359802245dfbfd633338d8b4dba3bc1

Observation 931333d2-c2b1-45a6-ae19-4998721a98ab · outbound

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

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Direct preference optimization: Your language model is secretly a reward model

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.672057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.672057Z digest=sha256:8af8e5529fc8b7ffc31d9a0e5cbf8a86f91db7f8acb5f11098a523de9400f85b

Observation f67a256f-1452-4d1e-8f3f-a9a1dc7bd5ef · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.735755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.735755Z digest=sha256:678c5e3178a9234e3551f12d61ff24f29f1ba2adcc7e1c1dbeca257f2f5a9ebb

Observation 73db049e-2451-4bf5-abaf-ef61e2eb777d · outbound

This paper cites Nousresearch/hermes-function-calling.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Nousresearch/hermes-function-calling

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:48:17.303862Z

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.

source=pdf_text observed=2026-08-06T20:48:14.787217Z digest=sha256:d6863044d4833d9ff05770d0207821b9d3ca720b0f20dd7fe35e20bd18fdeed9

Observation f8b2d1cd-4f00-4064-bb69-0a0ac1f66f11 · outbound

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

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.839589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.839589Z digest=sha256:7034dcdce7721ed6119b4f34fb7215db84059c14f561d62bda81237b727dc57c

Observation 1dadb1ff-70df-4e1c-b881-087864c2daf0 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:14.961604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:14.961604Z digest=sha256:958165beec58ef195901e5fa86129bee9689885d5b9c3005104238ceffbbd5b4

Observation a8f70119-f45e-4c48-a784-99fa5982f4bd · outbound

This paper cites Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Table.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Table

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.045521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.045521Z digest=sha256:41466450d9e812709e0f6c799c7dc94612061c53d514d9e25e37d43211cae090

Observation fadd12b9-712c-404f-9f73-edc7edfdb1b7 · outbound

This paper cites TAPAS: Weakly Supervised Table Parsing via Pre-training.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering TAPAS: Weakly Supervised Table Parsing via Pre-training

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.166374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.166374Z digest=sha256:42b299e0b36f4cef799b09bfba80717387b76c44ce111eb055b3480a687691f0

Observation 50de6d48-024b-4a36-bc2c-675945442484 · outbound

This paper cites TAPEX: Table Pre-training via Learning a Neural SQL Executor.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.279540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.279540Z digest=sha256:7504d116f9fb37e72b3c98e101ebfd3307e6fc4893314cfeb8bf468edad0a97c

Observation 71fb8287-afa3-40ed-9ce3-a0fb06077aa1 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Toolformer: Language models can teach themselves to use tools

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:48:16.945370Z

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.

source=pdf_text observed=2026-08-06T20:48:15.370495Z digest=sha256:aa1b14331aa219660c284327993075a1ff97b5bb0695cc7eccd931a7c031f146

Observation 34387c3c-32ce-457b-a532-3231b8bb10a2 · outbound

This paper cites The probabilistic relevance framework: Bm25 and beyond.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering The probabilistic relevance framework: Bm25 and beyond

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.454246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.454246Z digest=sha256:086f4e59b5e463b548b6adbd2dd35fc30c07c620ce69cf4943cd34833c1d932f

Observation 256ac739-9d68-46e1-bac1-e6e02b0c4297 · outbound

This paper cites Dense passage retrieval for open-domain question answering.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Dense passage retrieval for open-domain question answering

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.480811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.480811Z digest=sha256:501c4f6f5a72815e1b6c5f1569ef7439a02a54acd4678b7f3b50a42eedcd1b61

Observation 748e790b-1903-42b6-b4b0-0803b734cb77 · outbound

This paper cites {SparTA}:{Deep-Learning} model sparsity via {Tensor-with-Sparsity-Attribute}.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering {SparTA}:{Deep-Learning} model sparsity via {Tensor-with-Sparsity-Attribute}

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:48:16.633459Z

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.

source=pdf_text observed=2026-08-06T20:48:15.533821Z digest=sha256:7471bd8521ae174774bdc200da2ab68c2d60bec5fdfa800633655059d0b9c2bc

Observation 88da2eec-0652-48d4-94fc-69f44d5a0fdf · outbound

This paper cites Training language models to follow instructions with human feedback.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Training language models to follow instructions with human feedback

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:48:16.318880Z

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.

source=pdf_text observed=2026-08-06T20:48:15.610921Z digest=sha256:70d788252f9799f72e6881e481996f5b19e0f812f697b9363358313deb3fb95a

Observation d8b70dcc-1e13-4512-8cdd-c9ef4e083c3f · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:15.677456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:48:15.677456Z digest=sha256:9977b5a5bc1afb4190bb7bb6657c43d8e0bfaf229989babeeb808a2923b37915

Observation af8b5d05-6eaa-4d6b-a38f-8202b3ce594e · outbound

This paper cites Asynchronous methods for deep reinforcement learning.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering Asynchronous methods for deep reinforcement learning

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:48:16.117784Z

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.

source=pdf_text observed=2026-08-06T20:48:15.795768Z digest=sha256:c6131a8a7f2bb786e80c5e5d78070853eec84468c260cfd3a2544bd639f1f652

Pith citing papers

No inbound Pith citation observations are available.