Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:31:39.220992Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.21468.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:31:39.220992Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 789d64b4-69c1-41fb-80dd-51772945f630 · outbound
TopK Language Models How can we be so dense? the benefits of using highly sparse representations, 2019
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TopK Language Models Generating long sequences with sparse transformers, 2019
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TopK Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
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TopK Language Models [Full Post] Progress Update #1 from the GDM Mech Interp Team
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TopK Language Models Sparse autoencoders find highly interpretable features in language models, 2023
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TopK Language Models Detecting hallucinations in large language models using semantic entropy
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TopK Language Models The State of Sparse Training in Deep Reinforcement Learning
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TopK Language Models Memory-efficient transformers via top-k attention, 2021
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TopK Language Models Llama scope: Extracting millions of features from llama-3.1-8b with sparse autoencoders, 2024
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TopK Language Models Hindupur, Ekdeep Singh Lubana, Thomas Fel, and Demba Ba
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TopK Language Models Two Sparsities Are Better Than One: Unlocking the Performance Benefits of Sparse-Sparse Networks
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TopK Language Models How llms learn: Tracing internal representations with sparse autoencoders, 2025
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TopK Language Models Sparse is enough in scaling transformers, 2021
Reference 18
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TopK Language Models Saebench: A comprehensive benchmark for sparse autoen- coders in language model interpretability, 2025
Reference 20
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TopK Language Models Concept steerers: Leveraging k-sparse autoencoders for controllable generations, 2025
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TopK Language Models Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
Reference 22
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TopK Language Models Soft Threshold Weight Reparameterization for Learnable Sparsity
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TopK Language Models Sparse autoencoders do not find canonical units of analysis, 2025
Reference 24
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TopK Language Models Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2, 2024
Reference 25
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TopK Language Models Decoupled Weight Decay Regularization
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TopK Language Models Learning sparse neural networks through l_0 regularization
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TopK Language Models Fineweb-edu: the finest collection of educational content, 2024
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TopK Language Models Winner-take-all autoencoders
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TopK Language Models Pointer Sentinel Mixture Models
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TopK Language Models Can a suit of armor conduct electricity? a new dataset for open book question answering
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TopK Language Models Nguyen, Madeleine Gibescu, Antonio Liotta, and et al
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TopK Language Models The LAMBADA dataset: Word prediction requiring a broad discourse context
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TopK Language Models Sparse autoencoders trained on the same data learn different features, 2025
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TopK Language Models Automatically interpreting millions of features in large language models, 2024
Reference 35
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TopK Language Models The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale
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TopK Language Models Improving dictionary learning with gated sparse autoencoders, 2024
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TopK Language Models Winogrande: an adversarial winograd schema challenge at scale
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TopK Language Models Taking features out of superposition with sparse autoencoders
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TopK Language Models Outrageously large neural networks: The sparsely-gated mixture-of-experts layer, 2017
Reference 40
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TopK Language Models A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models, 2025
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TopK Language Models Codebook Features: Sparse and Discrete Interpretability for Neural Networks
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TopK Language Models Daniel Freeman, Theodore R
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TopK Language Models LLaMA: Open and Efficient Foundation Language Models
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TopK Language Models Meta Lingua: A minimal PyTorch LLM training library, 2024
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TopK Language Models Tracking the feature dynamics in llm training: A mechanistic study, 2025
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TopK Language Models STEP: Staged parameter-efficient pre-training for large language models
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TopK Language Models HellaSwag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics , pages 4791–4800, 2019
Reference 48
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TopK Language Models PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
Reference 49
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