Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts | Paper Citation Record

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This paper cites Attention is all you need,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Attention is all you need,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Language models are unsupervised multitask learners,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Language models are few-shot learners,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts ReAct: Synergizing reasoning and acting in language models,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts AutoGen: Enabling next-gen LLM applications via multi- agent conversation,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts When agents do not stop: Uncovering infinite agentic loops in LLM agents,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Syntax-guided synthesis,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Towards neural- network-guided program synthesis and verification,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Neu- ral networks and the Chomsky hierarchy,

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This paper cites On the translation of languages from left to right,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts On the translation of languages from left to right,

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This paper cites A survey and classification of controlled natural languages,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts A survey and classification of controlled natural languages,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts On systematically building a controlled natural language for functional requirements,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Retrieval-augmented generation for knowledge-intensive NLP tasks,

Reference 13

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Transformers are multi-state RNNs,

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This paper cites Theoretical limitations of self-attention in neural sequence models,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Theoretical limitations of self-attention in neural sequence models,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Saturated transformers are constant-depth threshold circuits,

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This paper cites The parallelism tradeoff: Limitations of log-precision transformers,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts The parallelism tradeoff: Limitations of log-precision transformers,

Reference 17

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This paper cites Hierarchies of memory limited computations,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Hierarchies of memory limited computations,

Reference 18

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This paper cites Formal language recognition by hard attention transformers: Perspectives from circuit complexity,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Formal language recognition by hard attention transformers: Perspectives from circuit complexity,

Reference 19

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts What formal languages can transformers express? A survey,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts On the ability and limitations of transformers to recognize formal languages,

Reference 21

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This paper cites Simplicity bias in transformers and their ability to learn sparse Boolean functions,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Simplicity bias in transformers and their ability to learn sparse Boolean functions,

Reference 22

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Unresolved cited work

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Unresolved cited work

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Visibly pushdown languages,

Reference 25

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Model-checking of ordered multi-pushdown automata,

Reference 26

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This paper cites Extracting automata from recur- rent neural networks using queries and counterexamples,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Extracting automata from recur- rent neural networks using queries and counterexamples,

Reference 27

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This paper cites Attention is Turing-complete,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Attention is Turing-complete,

Reference 28

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Learning to transduce with unbounded memory,

Reference 29

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Inferring algorithmic patterns with stack- augmented recurrent nets,

Reference 30

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This paper cites Learning context-free languages with non- deterministic stack RNNs,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Learning context-free languages with non- deterministic stack RNNs,

Reference 31

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Turing completeness of bounded- precision recurrent neural networks,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Stack attention: Improving the ability of transformers to model hierarchical patterns,

Reference 33

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Pushdown layers: Encoding recursive structure in transformer language models,

Reference 34

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Recursive transformer: Boosting reasoning ability with state stack,

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Transformer-XL: Attentive language models beyond a fixed-length context,

Reference 36

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Compressive transformers for long-range sequence modelling,

Reference 37

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Pretraining context compressor for large language models with embedding-based memory,

Reference 38

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts On the computational power of transformers and its implications in sequence modeling,

Reference 39

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Universal Transformers

Reference 40

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts The expressive power of transformers with chain of thought,

Reference 41

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Efficient Turing machine simulation with Trans- formers,

Reference 42

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Do transformers need deep long-range memory?

Reference 43

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Train short, test long: Attention with linear biases enables input length extrapolation,

Reference 44

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts The impact of positional encoding on length generalization in transformers,

Reference 45

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts RoFormer: En- hanced transformer with rotary position embedding,

Reference 46

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Base of RoPE bounds context length,

Reference 47

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Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Rotary positional embeddings as phase modulation: Theoretical bounds on the RoPE base for long-context transformers,

Reference 48

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This paper cites Towards re- vealing the mystery behind chain of thought: A theoretical perspective,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Towards re- vealing the mystery behind chain of thought: A theoretical perspective,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T06:04:38.146977Z

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Observation dfedf7ec-dd30-41ed-ad5e-dc822ad48c60 · outbound

This paper cites Benefits and Limitations of Communication in Multi-Agent Reasoning.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Benefits and Limitations of Communication in Multi-Agent Reasoning

Reference 50

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Observation 7c20dfd9-649e-42cc-9677-7c18928a7b50 · outbound

This paper cites Modeling tool use in transformers via computation oracles,.

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts Modeling tool use in transformers via computation oracles,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T06:04:38.256357Z

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