Paper Citation Record · LEDGER

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models

As of 19 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2505.07247.

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

pith.paper-citation-record.v1
2505.07247 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:25:37.576015Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T01:31:59.207857Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:06:59.574503Z

Reference resolution

55 of 55 outbound references displayed

verified exact2
verified fuzzy26
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67fbe111-a202-46c8-b410-e574b45b5b86 · outbound

This paper cites Automated essay scoring using discourse external knowledge,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Automated essay scoring using discourse external knowledge,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.912982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a261be39-31ca-4da5-83e0-f1df5bb8d924 · outbound

This paper cites Improve LLM-based Automatic Essay Scoring with Linguistic Features.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Improve LLM-based Automatic Essay Scoring with Linguistic Features

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.280015Z

Source-reported events for the cited work

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Observation 252dac85-dd2e-406a-9f94-fff6f6a7e2ae · outbound

This paper cites An automated essay scoring systems: a systematic literature review,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models An automated essay scoring systems: a systematic literature review,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.285968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2ed5a10-882d-4a1f-9aba-33ab95e0a017 · outbound

This paper cites Prompt Agnostic Essay Scorer: A Domain Generalization Approach to Cross-prompt Automated Essay Scoring.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Prompt Agnostic Essay Scorer: A Domain Generalization Approach to Cross-prompt Automated Essay Scoring

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.292005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9c6e080-0e50-47f4-bb20-8d2efc0137c3 · outbound

This paper cites Automated cross-prompt scoring of essay traits,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Automated cross-prompt scoring of essay traits,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.894874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 912ca936-70d2-4507-9245-d4e4244cc659 · outbound

This paper cites A short answer grading system in chinese by cnn,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models A short answer grading system in chinese by cnn,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.878163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 829ae285-d36a-4c41-8a0c-60318537ab5e · outbound

This paper cites A short answer grading system in chinese by support vector approach,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models A short answer grading system in chinese by support vector approach,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.860512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 386e1beb-863f-44e7-a6c0-d34bcc21ea38 · outbound

This paper cites GPT-4 Technical Report.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models GPT-4 Technical Report

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.320977Z

Source-reported events for the cited work

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Observation 55358dc4-2826-4d13-98f9-4e1707ff31c0 · outbound

This paper cites DeepSeek-V3 Technical Report.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models DeepSeek-V3 Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.327052Z

Source-reported events for the cited work

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Observation b4c81324-9f60-445b-aaa2-7dcd8871c39c · outbound

This paper cites Is llm-as-a-judge robust? investigating universal adversarial attacks on zero-shot LLM assessment,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Is llm-as-a-judge robust? investigating universal adversarial attacks on zero-shot LLM assessment,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.826092Z

Source-reported events for the cited work

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Observation 5c11d8d6-24ed-4e6f-9441-1b18a3f151d8 · outbound

This paper cites Beyond yes and no: Improving zero-shot LLM rankers via scoring fine-grained relevance labels,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Beyond yes and no: Improving zero-shot LLM rankers via scoring fine-grained relevance labels,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.339086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99d57d2b-b45f-4f1e-849e-bbd86b60f8e9 · outbound

This paper cites GLIDER: Grading LLM Interactions and Decisions using Explainable Ranking.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models GLIDER: Grading LLM Interactions and Decisions using Explainable Ranking

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.344350Z

Source-reported events for the cited work

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Observation 511f91b4-d53e-4cea-a979-f4fc8b288f8c · outbound

This paper cites The hewlett foundation: Automated essay scoring,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models The hewlett foundation: Automated essay scoring,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.794015Z

Source-reported events for the cited work

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Observation a965f117-da47-41b9-acdc-5bd224f349e7 · outbound

This paper cites Scaa: A dataset for automated short answer grading of children’s free-text answers in hindi and marathi,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Scaa: A dataset for automated short answer grading of children’s free-text answers in hindi and marathi,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.776588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 088ada9b-177a-4113-96e2-2227693bf7dc · outbound

This paper cites Semeval-2013 task 7: The joint student response analysis and 8th recognizing textual entailment challenge,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Semeval-2013 task 7: The joint student response analysis and 8th recognizing textual entailment challenge,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.759778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bf3115d5-c7e7-4a57-bbf6-9bd2d745b62a · outbound

This paper cites Automated long answer grading with ricechem dataset,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Automated long answer grading with ricechem dataset,

Reference 17

Resolution: verified exact; doi, observed 2026-08-15T22:25:37.729426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e1ba55a-c0ad-4ab8-b42f-bfd1716b1701 · outbound

This paper cites A new benchmark for automatic essay scoring in Portuguese,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models A new benchmark for automatic essay scoring in Portuguese,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.743082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cbc2963d-3deb-4e7b-8d79-9807ff684553 · outbound

This paper cites The hewlett foundation: Short answer scoring,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models The hewlett foundation: Short answer scoring,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.725844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation acbf8cb8-182e-4175-8775-11c8fd53b5a6 · outbound

This paper cites Automated short answer grading: A simple solution for a difficult task,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Automated short answer grading: A simple solution for a difficult task,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.843962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6afe4656-bf16-43bf-99da-d58bd0d25ca4 · outbound

This paper cites Text-to-text semantic similarity for automatic short answer grading,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Text-to-text semantic similarity for automatic short answer grading,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.709426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bad24b5e-2541-4b04-a955-c8261d244d3e · outbound

This paper cites M-sim: Multi-level semantic inference model for chinese short answer scoring in low-resource scenarios,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models M-sim: Multi-level semantic inference model for chinese short answer scoring in low-resource scenarios,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.394258Z

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Observation 9a5fcc17-45e1-4d69-a623-daaa37582af8 · outbound

This paper cites L-eval: Instituting standardized evaluation for long context language models,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models L-eval: Instituting standardized evaluation for long context language models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.398920Z

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Observation 2349f097-da85-4721-9716-150d5a970d50 · outbound

This paper cites Is ChatGPT a Good NLG Evaluator? A Preliminary Study.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Is ChatGPT a Good NLG Evaluator? A Preliminary Study

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.403992Z

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Observation 07c991bb-86cc-4b08-be06-421a1ecda4dd · outbound

This paper cites Large language models can accurately predict searcher preferences,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Large language models can accurately predict searcher preferences,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.409653Z

Source-reported events for the cited work

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Observation 96646ba5-160a-4a0e-b933-c3bb4f3c1727 · outbound

This paper cites Perspectives on large language models for relevance judgment,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Perspectives on large language models for relevance judgment,

Reference 26

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Observation dae34f46-775f-4dab-a7ee-37d877c99256 · outbound

This paper cites Enhancing transfer learning of llms through fine- tuning on task - related corpora for automated short-answer grading,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Enhancing transfer learning of llms through fine- tuning on task - related corpora for automated short-answer grading,

Reference 27

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Source-reported events for the cited work

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Observation d73afecf-e8c8-4978-b5e1-c7acc727f5b6 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.692860Z

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Observation 6582a659-2704-4c6c-b725-52ab8b99af63 · outbound

This paper cites JudgeLM: Fine-tuned Large Language Models are Scalable Judges.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models JudgeLM: Fine-tuned Large Language Models are Scalable Judges

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.430750Z

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Observation d502c796-fd84-42f1-8049-02881aedbc6c · outbound

This paper cites Calibrating llm-based evaluator,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Calibrating llm-based evaluator,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.677109Z

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Observation 5085b9eb-2aab-4a30-b7ae-9e5a56eea2ac · outbound

This paper cites Exploring LLM prompting strategies for joint essay scoring and feedback generation,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Exploring LLM prompting strategies for joint essay scoring and feedback generation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.657994Z

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Observation a11fa56b-b699-4441-93d1-0dd229a46bfd · outbound

This paper cites Knowledge distillation of llms for automatic scoring of science assessments,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Knowledge distillation of llms for automatic scoring of science assessments,

Reference 32

Resolution: verified exact; doi, observed 2026-08-15T22:25:38.639092Z

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Observation 78ac1071-4924-43a4-9fff-f65ff5ffe322 · outbound

This paper cites Efficient LLM comparative assessment: A product of experts framework for pairwise comparisons,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Efficient LLM comparative assessment: A product of experts framework for pairwise comparisons,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.621608Z

Source-reported events for the cited work

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Observation c269c917-9381-49f4-8d96-57aa088222ea · outbound

This paper cites Evaluating the Performance of Large Language Models on GAOKAO Benchmark.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 34

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Observation 54ae2945-2617-47e4-a733-106cf548c468 · outbound

This paper cites Asag2024: A combined benchmark for short answer grading,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Asag2024: A combined benchmark for short answer grading,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.602647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 52d578ba-2876-4185-a84b-e85747418324 · outbound

This paper cites Learning to grade short answer questions using semantic similarity measures and dependency graph alignments,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Learning to grade short answer questions using semantic similarity measures and dependency graph alignments,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.585881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 925e2821-4893-4ad6-a445-fead623247ff · outbound

This paper cites Short Answer Grading Using One-shot Prompting and Text Similarity Scoring Model.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Short Answer Grading Using One-shot Prompting and Text Similarity Scoring Model

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.472178Z

Source-reported events for the cited work

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Observation acd4b2d9-23c4-411b-b0d9-922849d098f3 · outbound

This paper cites Improving the performance of automatic short answer grading using transfer learning and augmentation,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Improving the performance of automatic short answer grading using transfer learning and augmentation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.568533Z

Source-reported events for the cited work

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Observation 8d7f6a0e-8165-41d1-8b43-f30162a0c3ec · outbound

This paper cites Rankcse: Unsupervised sentence representations learning via learning to rank,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Rankcse: Unsupervised sentence representations learning via learning to rank,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.488466Z

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Observation 686aa5dd-108c-432b-a090-a893239baf40 · outbound

This paper cites Diffcse: Difference-based contrastive learning for sentence embeddings,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Diffcse: Difference-based contrastive learning for sentence embeddings,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.494149Z

Source-reported events for the cited work

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Observation a7b0f1aa-06c5-4b17-a5de-eac4c2bdf49f · outbound

This paper cites The Llama 3 Herd of Models.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models The Llama 3 Herd of Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.500317Z

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Observation ae56ddeb-cae5-4be3-b1f8-96a9f14e3088 · outbound

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SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Qwen2 Technical Report

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.506787Z

Source-reported events for the cited work

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Observation 58b4a6ac-9710-4122-b4ce-d3c865d5e18d · outbound

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SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Qwen2.5 Technical Report

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.512994Z

Source-reported events for the cited work

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Observation 84584afa-9c5a-4e59-b8ff-b16473278719 · outbound

This paper cites Chatglm: A family of large language models from glm-130b to glm-4 all tools,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Chatglm: A family of large language models from glm-130b to glm-4 all tools,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.518394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71a9af5a-d4c3-4296-bc87-56f3fc752410 · outbound

This paper cites Mixtral of Experts.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Mixtral of Experts

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.523662Z

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Observation a7453a82-4f67-4c99-8a73-591823a94ac1 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.529198Z

Source-reported events for the cited work

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Observation d58c5dac-f04f-45c5-b45d-bbe6b83dd563 · outbound

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

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.534647Z

Source-reported events for the cited work

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Observation 5b056d15-8807-4cf6-8812-62df98e22eea · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Qwq-32b: Embracing the power of reinforcement learning,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.539755Z

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Observation 5f567276-c64d-448b-8881-337321c075f2 · outbound

This paper cites [Online].

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models [Online]

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.518609Z

Source-reported events for the cited work

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Observation 01067c15-d59f-4f01-a3af-d0f553581b28 · outbound

This paper cites Team, “Superdistillation achieves near-r1 performance with just 5.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Team, “Superdistillation achieves near-r1 performance with just 5

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.501567Z

Source-reported events for the cited work

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Observation 5dd7b017-bf1f-4171-b263-f0f7211e982a · outbound

This paper cites Mimo: Unlocking the reasoning potential of language model – from pretraining to posttraining,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Mimo: Unlocking the reasoning potential of language model – from pretraining to posttraining,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.474371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 14436c82-d65d-4ab5-bc33-000dfcc84204 · outbound

This paper cites Metamath: Bootstrap your own mathematical questions for large language models,.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Metamath: Bootstrap your own mathematical questions for large language models,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.448544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 16cc9b54-bef9-49e7-81fb-d12e7e169f9e · outbound

This paper cites - Independently evaluate each step: * Determine correctness ('label').

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models - Independently evaluate each step: * Determine correctness ('label')

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.430755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5d1ca454-5bb4-4f89-a8d1-d7e9a87204ba · outbound

This paper cites - Provide an overall evaluation ('label’).

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models - Provide an overall evaluation ('label’)

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.412132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 445126fd-d2be-47a6-82fd-0627bea49cd0 · outbound

This paper cites id": "Math_ShortAns_3.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models id": "Math_ShortAns_3

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:25:38.394516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1580b7cf-c95d-4dc3-9c56-74a12d5a4853 · outbound

This paper cites Available: https://doi.org/10.1016/j.engappai.2023.106292.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Available: https://doi.org/10.1016/j.engappai.2023.106292

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T22:25:37.483240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation abf010d1-098e-4099-99b2-b8a950e31a72 · inbound

EDIT: Evidence-Diagnosed Intervention Training for Rule-Faithful LLM Grading cites this paper.

EDIT: Evidence-Diagnosed Intervention Training for Rule-Faithful LLM Grading SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:06:59.575912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.