Paper Citation Record · LEDGER

An Analysis for Reasoning Bias of Language Models with Small Initialization

As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 6 inbound Pith citation observations for arXiv:2502.04375.

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

pith.paper-citation-record.v1
2502.04375 v2

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:28:52.279862Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:01:15.054309Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T20:05:04.830513Z

Reference resolution

60 of 60 outbound references displayed

verified exact3
verified fuzzy17
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e863a94a-9e15-4fd7-a0af-a7c4fd290b6a · outbound

This paper cites Phi-4 Technical Report.

An Analysis for Reasoning Bias of Language Models with Small Initialization Phi-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.220951Z

Source-reported events for the cited work

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Observation 572a90c5-ba55-436e-9ae3-e26e705ce555 · outbound

This paper cites GPT-4 Technical Report.

An Analysis for Reasoning Bias of Language Models with Small Initialization GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.227174Z

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Observation 7612f387-27eb-47fa-9cf5-e1ead065d700 · outbound

This paper cites S., Hu, W., Li, Z., Salakhutdinov, R.

An Analysis for Reasoning Bias of Language Models with Small Initialization S., Hu, W., Li, Z., Salakhutdinov, R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.666924Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bb436b54-89ab-415d-bcfc-f53260046733 · outbound

This paper cites Reflections after refereeing papers for nips.

An Analysis for Reasoning Bias of Language Models with Small Initialization Reflections after refereeing papers for nips

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.616478Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 01915d98-d04e-4ebe-9319-62ae92630134 · outbound

This paper cites and Rathie, P.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Rathie, P

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.525810Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7280dc0a-53e8-4036-8f73-99b8c833acf1 · outbound

This paper cites an unresolved cited work.

An Analysis for Reasoning Bias of Language Models with Small Initialization Unresolved cited work

Reference 6

Resolution: verified exact; doi, observed 2026-08-09T05:28:52.349960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d67c68a-3e61-4241-829f-9a3692893d1b · outbound

This paper cites and Bach, F.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Bach, F

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.464356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2ed755b8-7569-4ff0-89d1-601a80a9f9b5 · outbound

This paper cites Faithful Reasoning Using Large Language Models.

An Analysis for Reasoning Bias of Language Models with Small Initialization Faithful Reasoning Using Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.257146Z

Source-reported events for the cited work

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Observation 54507407-694a-4d15-9c72-0177863cc7de · outbound

This paper cites Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning.

An Analysis for Reasoning Bias of Language Models with Small Initialization Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.262280Z

Source-reported events for the cited work

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Observation ece0bfbf-5f29-4af2-8523-40b8fc116d48 · outbound

This paper cites The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization.

An Analysis for Reasoning Bias of Language Models with Small Initialization The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.278903Z

Source-reported events for the cited work

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Observation 36299e03-8cb4-4498-8d23-30005147fb43 · outbound

This paper cites CTL++: Evaluating Generalization on Never-Seen Compositional Patterns of Known Functions, and Compatibility of Neural Representations.

An Analysis for Reasoning Bias of Language Models with Small Initialization CTL++: Evaluating Generalization on Never-Seen Compositional Patterns of Known Functions, and Compatibility of Neural Representations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.310278Z

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Observation 8344b049-1e7f-4a95-9e9d-78aca8964860 · outbound

This paper cites L., Jiang, L., Lin, B.

An Analysis for Reasoning Bias of Language Models with Small Initialization L., Jiang, L., Lin, B

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.343200Z

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Observation 5c83dc4b-a778-4551-9439-c7bc29679656 · outbound

This paper cites A comparative analysis of optimization and generalization properties of two-layer neural network and random feature models under gradient descent dynamics.

An Analysis for Reasoning Bias of Language Models with Small Initialization A comparative analysis of optimization and generalization properties of two-layer neural network and random feature models under gradient descent dynamics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.422368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 73bb8b33-8326-404f-a4e5-7a52f025a538 · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

An Analysis for Reasoning Bias of Language Models with Small Initialization TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.403494Z

Source-reported events for the cited work

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Observation f571c1fe-67d4-478d-84f4-639840cf1a11 · outbound

This paper cites How does gpt obtain its ability? tracing emergent abilities of language models to their sources.

An Analysis for Reasoning Bias of Language Models with Small Initialization How does gpt obtain its ability? tracing emergent abilities of language models to their sources

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.406308Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 671aca84-d7a9-4b9b-b25c-0c7a3538cda2 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

An Analysis for Reasoning Bias of Language Models with Small Initialization Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.501648Z

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Observation bce18684-9761-4eff-b1b7-d8fc826d7f09 · outbound

This paper cites S., Perez, F., Ba, J., and Volkovs, M.

An Analysis for Reasoning Bias of Language Models with Small Initialization S., Perez, F., Ba, J., and Volkovs, M

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.379227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eefeb4ba-6f10-4d26-85c3-dcebc66f833d · outbound

This paper cites Learning compositionally through attentive guidance.

An Analysis for Reasoning Bias of Language Models with Small Initialization Learning compositionally through attentive guidance

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-09T05:28:52.745846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0fa9d1e1-9024-4aa2-bee3-4c2504ddd66c · outbound

This paper cites Neural Tangent Kernel : Convergence and Generalization in Neural Networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization Neural Tangent Kernel : Convergence and Generalization in Neural Networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.363554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 718e5914-bfe6-4e6b-88e0-52a57fd03c0d · outbound

This paper cites B., and M \"u ller, K.

An Analysis for Reasoning Bias of Language Models with Small Initialization B., and M \"u ller, K

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.562035Z

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Observation d68ae65b-4b0e-4cc9-9b77-c09de6140f3c · outbound

This paper cites Break It Down: Evidence for Structural Compositionality in Neural Networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization Break It Down: Evidence for Structural Compositionality in Neural Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.566749Z

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Observation f9f4ffcc-a086-4b30-9e69-316ee80546cf · outbound

This paper cites Not all tokens are what you need for pretraining.

An Analysis for Reasoning Bias of Language Models with Small Initialization Not all tokens are what you need for pretraining

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.571389Z

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Observation 7d20637e-1d00-4009-a74c-95afaac33a48 · outbound

This paper cites DeepSeek-V3 Technical Report.

An Analysis for Reasoning Bias of Language Models with Small Initialization DeepSeek-V3 Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.575637Z

Source-reported events for the cited work

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Observation 276bfca0-e664-4254-95a6-d80ad59018ca · outbound

This paper cites Transformers Learn Shortcuts to Automata.

An Analysis for Reasoning Bias of Language Models with Small Initialization Transformers Learn Shortcuts to Automata

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.580568Z

Source-reported events for the cited work

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Observation a35bad4b-12e6-4bb5-9f02-49f411c4d22c · outbound

This paper cites Understanding the Difficulty of Training Transformers.

An Analysis for Reasoning Bias of Language Models with Small Initialization Understanding the Difficulty of Training Transformers

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.585595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17c8b97d-acaf-48b7-b6b2-195ea4becdf4 · outbound

This paper cites J., Ma, Z., and Zhang, Y.

An Analysis for Reasoning Bias of Language Models with Small Initialization J., Ma, Z., and Zhang, Y

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.319975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c396f774-5388-4fc7-85ab-05341015456f · outbound

This paper cites an unresolved cited work.

An Analysis for Reasoning Bias of Language Models with Small Initialization Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.594177Z

Source-reported events for the cited work

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Observation 318fdf09-8ad9-422b-8499-08325e10cf91 · outbound

This paper cites A mean field view of the landscape of two-layer neural networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization A mean field view of the landscape of two-layer neural networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.598613Z

Source-reported events for the cited work

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Observation e96eff98-44a6-4c7b-af36-3131d9171e0c · outbound

This paper cites Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task.

An Analysis for Reasoning Bias of Language Models with Small Initialization Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.603410Z

Source-reported events for the cited work

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Observation 18875ebd-5a96-486f-883c-61a8d0949742 · outbound

This paper cites Language models are unsupervised multitask learners.

An Analysis for Reasoning Bias of Language Models with Small Initialization Language models are unsupervised multitask learners

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.620847Z

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Observation 857d318c-56eb-4190-b762-acc542225018 · outbound

This paper cites Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks.

An Analysis for Reasoning Bias of Language Models with Small Initialization Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.641065Z

Source-reported events for the cited work

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Observation e81b832a-d782-4d54-97f1-9355dea9d994 · outbound

This paper cites and Vanden-Eijnden, E.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Vanden-Eijnden, E

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.285195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82d661f1-f854-4d06-8bfb-bd376c14dbac · outbound

This paper cites and He, H.

An Analysis for Reasoning Bias of Language Models with Small Initialization and He, H

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.269539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 485a5d23-6b5d-4d98-8247-abf04b726b2d · outbound

This paper cites and Spiliopoulos, K.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Spiliopoulos, K

Reference 34

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Source-reported events for the cited work

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Observation 6756689a-d32d-49bd-9937-a4f787d68eb8 · outbound

This paper cites Neurocompositional computing: From the central paradox of cognition to a new generation of ai systems.

An Analysis for Reasoning Bias of Language Models with Small Initialization Neurocompositional computing: From the central paradox of cognition to a new generation of ai systems

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.255005Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 42c48d34-487b-4c4c-a673-849b591f0d9d · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

An Analysis for Reasoning Bias of Language Models with Small Initialization Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.788616Z

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Observation 58695419-ce1f-4005-9824-f486b8936afa · outbound

This paper cites and Kolter, J.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Kolter, J

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.239723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4569c100-5d1e-4abf-bf1c-3329d336f44d · outbound

This paper cites Deepnet: Scaling transformers to 1,000 layers.

An Analysis for Reasoning Bias of Language Models with Small Initialization Deepnet: Scaling transformers to 1,000 layers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.224112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bd5896f8-8a41-4384-8067-67e48f6e9198 · outbound

This paper cites Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning.

An Analysis for Reasoning Bias of Language Models with Small Initialization Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.801401Z

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Observation be13f3e7-9ac0-4b58-9233-54524425ebdd · outbound

This paper cites Improving Generalization and Convergence by Enhancing Implicit Regularization.

An Analysis for Reasoning Bias of Language Models with Small Initialization Improving Generalization and Convergence by Enhancing Implicit Regularization

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-09T05:28:52.592722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ed352f33-948f-4aad-a02e-453e9df0eec5 · outbound

This paper cites Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling.

An Analysis for Reasoning Bias of Language Models with Small Initialization Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.810922Z

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Observation 39617b73-84ee-4467-93fb-da96bb31208f · outbound

This paper cites Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism.

An Analysis for Reasoning Bias of Language Models with Small Initialization Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.815997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd478da5-6f8d-4d05-b085-6e5dad8133da · outbound

This paper cites H., Hashimoto, T., Vinyals, O., Liang, P., Dean, J., and Fedus, W.

An Analysis for Reasoning Bias of Language Models with Small Initialization H., Hashimoto, T., Vinyals, O., Liang, P., Dean, J., and Fedus, W

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.199486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b2f1df8b-9f3c-4c1d-b4b7-40cc19ef6a2f · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

An Analysis for Reasoning Bias of Language Models with Small Initialization Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.824742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb5e145f-64c4-4f27-bd06-d99b826300bc · outbound

This paper cites Gradient Dynamics of Shallow Univariate ReLU Networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization Gradient Dynamics of Shallow Univariate ReLU Networks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.829313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ea9d09-8e59-40d0-912b-10b067bfa388 · outbound

This paper cites An overview of condensation phenomenon in deep learning.

An Analysis for Reasoning Bias of Language Models with Small Initialization An overview of condensation phenomenon in deep learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.834240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54c580f6-6c77-4e44-9636-09a75b1d5d17 · outbound

This paper cites Do Vision-Language Pretrained Models Learn Composable Primitive Concepts?.

An Analysis for Reasoning Bias of Language Models with Small Initialization Do Vision-Language Pretrained Models Learn Composable Primitive Concepts?

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.838929Z

Source-reported events for the cited work

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Observation 172990d3-9470-4d19-b1b3-d190604287c2 · outbound

This paper cites Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention.

An Analysis for Reasoning Bias of Language Models with Small Initialization Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.843650Z

Source-reported events for the cited work

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Observation fe9d802e-28cb-41b2-a937-ba971030ca36 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

An Analysis for Reasoning Bias of Language Models with Small Initialization Understanding deep learning requires rethinking generalization

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.848843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38bcef4a-6788-4061-a647-f77c37aae9d4 · outbound

This paper cites A type of generalization error induced by initialization in deep neural networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization A type of generalization error induced by initialization in deep neural networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.853798Z

Source-reported events for the cited work

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Observation add21f00-2939-48fa-90f9-e7ad69b09681 · outbound

This paper cites Linear Stability Hypothesis and Rank Stratification for Nonlinear Models.

An Analysis for Reasoning Bias of Language Models with Small Initialization Linear Stability Hypothesis and Rank Stratification for Nonlinear Models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.858900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f822a794-272e-45e8-9b20-e0794a811df3 · outbound

This paper cites Loss Spike in Training Neural Networks.

An Analysis for Reasoning Bias of Language Models with Small Initialization Loss Spike in Training Neural Networks

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.863442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c412bb4-6094-4512-b027-703e74fbdc37 · outbound

This paper cites and Xu, Z.-Q.

An Analysis for Reasoning Bias of Language Models with Small Initialization and Xu, Z.-Q

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:28:53.141956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a52381c9-da47-499e-8db9-e5007416eeac · outbound

This paper cites Stochastic Modified Equations and Dynamics of Dropout Algorithm.

An Analysis for Reasoning Bias of Language Models with Small Initialization Stochastic Modified Equations and Dynamics of Dropout Algorithm

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:52.046608Z

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Observation ec5d6f10-a553-4fa8-b59c-f0dcbcacc58d · outbound

This paper cites an unresolved cited work.

An Analysis for Reasoning Bias of Language Models with Small Initialization Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:28:53.029678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ef590fc0-5244-4723-aa78-0af3468e01e1 · outbound

This paper cites Anchor function: a type of benchmark functions for studying language models.

An Analysis for Reasoning Bias of Language Models with Small Initialization Anchor function: a type of benchmark functions for studying language models

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This paper cites Complexity Control Facilitates Reasoning-Based Compositional Generalization in Transformers.

An Analysis for Reasoning Bias of Language Models with Small Initialization Complexity Control Facilitates Reasoning-Based Compositional Generalization in Transformers

Reference 57

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An Analysis for Reasoning Bias of Language Models with Small Initialization Unresolved cited work

Reference 58

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This paper cites R., and Goldstein, T.

An Analysis for Reasoning Bias of Language Models with Small Initialization R., and Goldstein, T

Reference 59

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This paper cites write newline.

An Analysis for Reasoning Bias of Language Models with Small Initialization write newline

Reference 60

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Pith citing papers

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An overview of condensation phenomenon in deep learning cites this paper.

An overview of condensation phenomenon in deep learning An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 17

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Observation b8fc0767-8d84-497a-abfa-5756056ee175 · inbound

Scalable Complexity Control Facilitates Reasoning Ability of LLMs cites this paper.

Scalable Complexity Control Facilitates Reasoning Ability of LLMs An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 73

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Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge cites this paper.

Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 34

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Observation a616f226-79c2-4b59-a397-8de0f7fbb763 · inbound

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability cites this paper.

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 20

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Observation 1c17a3da-46b0-4515-aaf6-d2123e7139f9 · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 3

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Observation 978df83f-d197-48a9-84d2-e4b6899c320e · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis An Analysis for Reasoning Bias of Language Models with Small Initialization

Reference 2

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