LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning | Paper Citation Record

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

Language Models (Mostly) Know What They Know LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 206

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The Falcon Series of Open Language Models cites this paper.

The Falcon Series of Open Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 54

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Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models cites this paper.

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 228

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Sparse Upcycling: Inference Inefficient Finetuning cites this paper.

Sparse Upcycling: Inference Inefficient Finetuning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 18

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Cross-Modal Consistency in Multimodal Large Language Models cites this paper.

Cross-Modal Consistency in Multimodal Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 12

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Understanding Chain-of-Thought in LLMs through Information Theory cites this paper.

Understanding Chain-of-Thought in LLMs through Information Theory LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 19

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GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI cites this paper.

GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 47

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Mixture of Hidden-Dimensions Transformer cites this paper.

Mixture of Hidden-Dimensions Transformer LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 25

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Can OpenAI o1 outperform humans in higher-order cognitive thinking? cites this paper.

Can OpenAI o1 outperform humans in higher-order cognitive thinking? LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 50

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Lillama: Large Language Models Compression via Low-Rank Feature Distillation cites this paper.

Lillama: Large Language Models Compression via Low-Rank Feature Distillation LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 28

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NExtLong: Toward Effective Long-Context Training without Long Documents cites this paper.

NExtLong: Toward Effective Long-Context Training without Long Documents LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 60

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Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models cites this paper.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 27

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JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models cites this paper.

JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 21

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Lightweight and Post-Training Structured Pruning for On-Device Large Lanaguage Models cites this paper.

Lightweight and Post-Training Structured Pruning for On-Device Large Lanaguage Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 41

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MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models cites this paper.

MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 14

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ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning cites this paper.

ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 7

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Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging cites this paper.

Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 29

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Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining cites this paper.

Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 23

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DarwinLM: Evolutionary Structured Pruning of Large Language Models cites this paper.

DarwinLM: Evolutionary Structured Pruning of Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 15

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MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections cites this paper.

MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 29

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DONOD: Efficient and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning cites this paper.

DONOD: Efficient and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 22

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Computational Reasoning of Large Language Models cites this paper.

Computational Reasoning of Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 43

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RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection cites this paper.

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 41

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GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining cites this paper.

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 20

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UAQFact: Evaluating Factual Knowledge Utilization of LLMs on Unanswerable Questions cites this paper.

UAQFact: Evaluating Factual Knowledge Utilization of LLMs on Unanswerable Questions LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 23

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R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation cites this paper.

R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 26

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VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL cites this paper.

VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 20

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Advantageous Parameter Expansion Training Makes Better Large Language Models cites this paper.

Advantageous Parameter Expansion Training Makes Better Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 48

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Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning cites this paper.

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

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Reason from Future: Reverse Thought Chain Enhances LLM Reasoning cites this paper.

Reason from Future: Reverse Thought Chain Enhances LLM Reasoning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 10

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GTA: Grouped-head latenT Attention cites this paper.

GTA: Grouped-head latenT Attention LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 35

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ReasonBridge: Efficient Reasoning Transfer from Closed to Open-Source Language Models cites this paper.

ReasonBridge: Efficient Reasoning Transfer from Closed to Open-Source Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 31

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models cites this paper.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 36

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Degrees of Freedom for Linear Attention: Distilling Softmax Attention with Optimal Feature Efficiency cites this paper.

Degrees of Freedom for Linear Attention: Distilling Softmax Attention with Optimal Feature Efficiency LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 2011

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Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? cites this paper.

Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

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Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 108

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GeLaCo: An Evolutionary Approach to Layer Compression cites this paper.

GeLaCo: An Evolutionary Approach to Layer Compression LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 28

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Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.

Language Models Improve When Pretraining Data Matches Target Tasks LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 59

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Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training cites this paper.

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 20

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LLM Data Selection and Utilization via Dynamic Bi-level Optimization cites this paper.

LLM Data Selection and Utilization via Dynamic Bi-level Optimization LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

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Rethinking Reasoning Quality in Large Language Models through Enhanced Chain-of-Thought via RL cites this paper.

Rethinking Reasoning Quality in Large Language Models through Enhanced Chain-of-Thought via RL LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 28

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BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining cites this paper.

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 43

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DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone cites this paper.

DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 17

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MIDUS: Memory-Infused Depth Up-Scaling cites this paper.

MIDUS: Memory-Infused Depth Up-Scaling LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 17

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NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.

NVIDIA Nemotron 3: Efficient and Open Intelligence LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 140

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Reasoning or Fluency? Dissecting Probabilistic Confidence in Best-of-N Selection cites this paper.

Reasoning or Fluency? Dissecting Probabilistic Confidence in Best-of-N Selection LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 2023

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Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization cites this paper.

Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 9

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DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent cites this paper.

DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 2020

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SAGE: A Service Agent Graph-guided Evaluation Benchmark cites this paper.

SAGE: A Service Agent Graph-guided Evaluation Benchmark LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 29

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Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance cites this paper.

Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 25

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KoCo: Conditioning Language Model Pre-training on Knowledge Coordinates cites this paper.

KoCo: Conditioning Language Model Pre-training on Knowledge Coordinates LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 1

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Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods cites this paper.

Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 24

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Logic-Regularized Verifier Elicits Reasoning from LLMs cites this paper.

Logic-Regularized Verifier Elicits Reasoning from LLMs LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 24

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Bridging the Missing-Modality Gap: Improving Text-Only Calibration of Vision Language Models cites this paper.

Bridging the Missing-Modality Gap: Improving Text-Only Calibration of Vision Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T21:43:00.203942Z

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 da46f8ba-74f5-4c69-9501-908fa3f5d3e8 · inbound

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy cites this paper.

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-29T21:53:59.560432Z

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 f7afbc56-8141-4d18-930f-a44b83aa33ab · inbound

DenseSteer: Steering Small Language Models towards Dense Math Reasoning cites this paper.

DenseSteer: Steering Small Language Models towards Dense Math Reasoning LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-29T07:53:13.951628Z

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 de9d8600-518f-4cee-ae65-5fdf2e41ac75 · inbound

Evaluating Interactive Reasoning in Large Language Models: A Hierarchical Benchmark with Executable Games cites this paper.

Evaluating Interactive Reasoning in Large Language Models: A Hierarchical Benchmark with Executable Games LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T17:53:47.441976Z

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 4dd3f2bf-ec7d-414e-86af-092b2a32b8e5 · inbound

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs cites this paper.

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:12:25.237086Z

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 489123d4-9d43-41e4-af03-6104752a8a4d · inbound

RegMix-D: Dynamic Data Mixing via Proxy Training Trajectories cites this paper.

RegMix-D: Dynamic Data Mixing via Proxy Training Trajectories LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T00:39:17.537323Z

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 cfc88b29-6b10-4ba2-808e-69946c0b1154 · inbound

HOLMES: Evaluating Higher-Order Logical Reasoning in LLMs cites this paper.

HOLMES: Evaluating Higher-Order Logical Reasoning in LLMs LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:46.364749Z

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 54035e00-56bb-44a8-a619-1c8075a0c0c8 · inbound

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling cites this paper.

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:32.555584Z

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 e07c6e72-e3bd-4527-a771-873bb218ba70 · inbound

PACE: A Proxy for Agentic Capability Evaluation cites this paper.

PACE: A Proxy for Agentic Capability Evaluation LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:38:18.465142Z

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 87d728b4-7bbb-4cdf-b4bb-403824efb364 · inbound

PACE: A Proxy for Agentic Capability Evaluation cites this paper.

PACE: A Proxy for Agentic Capability Evaluation LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T08:29:58.561496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 540c74c9-79ea-4f6e-b006-bed4a2a8b05c · inbound

Efficient Decentralized Multi-task Dataset Valuation via Model Merging cites this paper.

Efficient Decentralized Multi-task Dataset Valuation via Model Merging LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-12T03:07:59.787733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9b8603e-2b4d-492b-8e0e-7ff25382427d · inbound

Non-vacuous Generalization Bounds for Reinforcement Learning with Verifiable Rewards cites this paper.

Non-vacuous Generalization Bounds for Reinforcement Learning with Verifiable Rewards LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T02:01:53.579164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cbe41f1-994d-42c5-b755-0e9569b9af4b · inbound

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory cites this paper.

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T23:07:18.062768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f510c909-b3b8-4651-9d7c-aff003f4ddf3 · inbound

What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs cites this paper.

What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T02:46:49.714329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers