Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-11T02:23:52.589354Z
Paper Citation Record · LEDGER
As of 5 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2605.07271.
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 2026-05-11T02:23:52.589354Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-14T09:09:29.470093Z
A source-named dated measurement, never combined with another source.
Source: cited_works
61 of 61 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 59610408-a183-405d-a06c-268908c01d12 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions LLaMA: Open and Efficient Foundation Language Models
Reference 1
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Reference 3
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Introducing Qwen1.5 , url =
Reference 4
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Qwen2 Technical Report
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions arXiv e-prints , pages=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions International Conference on Machine Learning , pages=
Reference 9
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Findings of the Association for Computational Linguistics: ACL 2025 , pages=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics , year=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Advances in neural information processing systems , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions ArXiv , year=
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Observation 0c0a9ab6-697e-47d3-b600-4810adc0051b · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Transferring Core Knowledge via Learngenes
Reference 21
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Advances in Neural Information Processing Systems , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 24
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 27
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Observation cddb2aaa-c23f-4a4c-ae77-8b645044def7 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Extracting Multimodal Learngene in CLIP: Unveiling the Multimodal Generalizable Knowledge
Reference 28
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Observation 0af29fda-5911-40be-ae0f-fae5eba37e3c · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Forty-first International Conference on Machine Learning , year=
Reference 29
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI conference on artificial intelligence , volume=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions NAACL , year =
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the International Conference on Learning Representations (ICLR) , year=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the International Conference on Learning Representations (ICLR) , year=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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Observation 038d7afa-0ff8-4214-83fd-66a97b849786 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks
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Observation c4ace4a4-b991-4d03-bee9-bcd547767642 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions International conference on machine learning , pages=
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions 2020 , month =
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Observation d6792c96-ec4b-42a9-94b2-3d03e6383420 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Understanding intermediate layers using linear classifier probes
Reference 45
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Observation 6534c5bc-fdd7-4e0a-84e9-5b40cff9ebeb · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Reference 46
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Observation f2ed4a13-39a3-4aff-82a5-6d97f554cb29 · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Eliciting Latent Predictions from Transformers with the Tuned Lens
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Piqa: Reasoning about physical commonsense in natural language
Reference 48
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Boolq: Exploring the surprising difficulty of natural yes/no questions
Reference 49
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Observation 1458d9a8-cd44-418c-a060-c42f4bf1bd3b · outbound
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 50
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions The llama 3 herd of models
Reference 51
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions The Unreasonable Ineffectiveness of the Deeper Layers
Reference 52
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Measuring massive multitask language understanding
Reference 53
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods
Reference 54
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Similarity of neural network representations revisited
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Losparse: Structured compression of large language models based on low-rank and sparse approximation
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging
Reference 57
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Llm-pruner: On the structural pruning of large language models
Reference 58
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Shortgpt: Layers in large language models are more redundant than you expect
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Interpreting GPT : the logit lens
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions In-context Learning and Induction Heads
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Ig-pruning: Input-guided block pruning for large language models
Reference 62
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Winogrande: An adversarial winograd schema challenge at scale
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Building variable-sized models via learngene pool
Reference 64
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Pocketllm: Ultimate compression of large language models via meta networks
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Llama 2: Open Foundation and Fine-Tuned Chat Models
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Layer as puzzle pieces: Compressing large language models through layer concatenation
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Learngene: Inheriting Condensed Knowledge from the Ancestry Model to Descendant Models
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Vision transformers as probabilistic expansion from learngene
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Learngene: From open-world to your learning task
Reference 70
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions LogitLens4LLMs: Extending Logit Lens Analysis to Modern Large Language Models
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models
Reference 73
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Reference 74
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions LaCo: Large Language Model Pruning via Layer Collapse
Reference 75
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Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Reference 76
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Source-reported events for the cited work
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