Pith. sign in

Paper Citation Record · LEDGER

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning

As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2607.28478.

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

pith.paper-citation-record.v1
2607.28478 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T06:09:53.848261Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa1be9c2-ad21-4039-93fb-4dcdf78b16a9 · outbound

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

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.803423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.803423Z digest=sha256:53e8fa3f34f69f932935118b92412bc6d1b273105c48e5b107385f75e307252e

Observation 1e2dac50-5fa5-4b41-9274-9c58a581226e · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Measuring Mathematical Problem Solving With the MATH Dataset

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.808384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.808384Z digest=sha256:742f75751fe4bde156ec49f7f958156c6604f9853cb55a9d3786c1f56661b396

Observation b99c1898-30c6-47b5-8ff1-b27a9e42b8f7 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Language Models (Mostly) Know What They Know

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.812762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.812762Z digest=sha256:5be81b5145df51985e0786f7e945e65ad2a5929e100540caed14611ae81e8fb7

Observation b629b9d2-5030-459d-b35f-8000bef25eb4 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.821520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.821520Z digest=sha256:f5d97758a860f48ebdba4cd882a2b960e1076578070942c33efaaece65e66d85

Observation cdd48a53-91e2-47d3-ab5f-392fefe0bfb4 · outbound

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

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.830262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.830262Z digest=sha256:7b1f16219fca7c73336d0847c640946dfd5553b58c084fa20082e56323de515b

Observation 794bdeb9-70a2-4de7-a4fe-f20b6940acf0 · outbound

This paper cites A Survey on (M)LLM-Based GUI Agents.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning A Survey on (M)LLM-Based GUI Agents

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.835065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.835065Z digest=sha256:af12017e22d41ad762fd6b37e30b4fb4f84fb86d4d945036e3c7d725c08fc11d

Observation 420473a3-06ab-4a5b-bd4b-326772e6c33c · outbound

This paper cites On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.839702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.839702Z digest=sha256:4a106cac745d4edaf204d0f51d4ea5a15aa362d7ae2387fa57e5a6c9665832df

Observation ebe366e1-fbcf-4933-aacc-1a382e9c61ca · outbound

This paper cites arXiv preprint arXiv:2606.19348.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning arXiv preprint arXiv:2606.19348

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.843741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.843741Z digest=sha256:3ac9156d3e9d8f262348e89cdfd273e95c69989ac68d53dabc9ca7ae604a88a5

Observation 3a691680-8a9b-4898-be7b-aa70780e267b · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning GLM-5: from Vibe Coding to Agentic Engineering

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.848261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.848261Z digest=sha256:8329301a2ea453b68d52b7bb2b098041341ee948800293c8ab13407f59eb022a

Observation 9ef9fb48-ccf3-4de4-af13-01bbb9f1f6b4 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Training Verifiers to Solve Math Word Problems

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.794368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.794368Z digest=sha256:ba02e013dfa07d80d9e7ca2e455323e3a13a8eb191a5b00cc10c7f02df952779

Observation ac68297a-2c1a-4572-bd3c-bfa32b625260 · outbound

This paper cites Advances in Neural Information Processing Systems, 35: 22199–22213.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Advances in Neural Information Processing Systems, 35: 22199–22213

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.817130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.817130Z digest=sha256:15aa7aa88f90ce50ac9927ecf9c77064e31422e3cbf4471ef1bf9ccf9f179863

Observation c15ca3b9-25e9-4f5f-9c54-2f1ed10911c0 · outbound

This paper cites Qin, Y.; Liang, S.; Ye, Y.; Zhu, K.; Yan, L.; Lu, Y.; Lin, Y.; Cong,X.;Tang,X.; Qian,B.;etal.2024.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Qin, Y.; Liang, S.; Ye, Y.; Zhu, K.; Yan, L.; Lu, Y.; Lin, Y.; Cong,X.;Tang,X.; Qian,B.;etal.2024

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.826170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.826170Z digest=sha256:ad7645441d30eda96802060d0ebf630c14eb7c9f21cd424269f0483fe68354f0

Observation 9dc8cc7d-9327-4632-857a-963514e45964 · outbound

This paper cites Anthropic.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Anthropic

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.783917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.783917Z digest=sha256:4fb84e7f39e629439daf36a7f52f0e1e5ca6e49b263b7b1ae3730bc7802955c3

Observation 2bb5d5c7-9a11-4a3a-bd1a-20c60de77682 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.799000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.799000Z digest=sha256:e670e5b9833f551be4cfdeaf1ed7ef68395adca5b37b394c6fe50be9c4b6e611

Observation b5139b2e-c09d-4c62-b2eb-07db4cafe6c8 · outbound

This paper cites The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence.

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-07-31T06:09:53.789633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T06:09:53.789633Z digest=sha256:480d9832c1b6f3bd6419d7ddc5a8edb8b53d9e12c0b222b3ece2da06f9e5a17f

Pith citing papers

No inbound Pith citation observations are available.