Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T08:18:33.455530Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2607.21677.
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 2026-08-01T08:18:33.455530Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
60 of 60 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation c7479739-f648-4380-acc0-b26e3df43081 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Cwm: An open-weights llm for research on code generation with world models,
Reference 1
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Observation 2e20222e-9191-48bf-9870-c0b62c0d000f · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks
Reference 2
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Observation ce525bee-d77b-4a8f-9513-c3cf13ee0fdd · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Qwen3-Coder-Next Technical Report
Reference 3
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Observation 55787193-6cbe-4b61-9d49-3fc484fe605d · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Mixtral of Experts
Reference 4
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Observation cb6a4e8e-579d-4d60-a3e8-49a78dbc040d · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy How much do language models memorize?
Reference 5
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Observation b2e04504-54c9-451d-a8a5-c241aba4437c · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
Reference 6
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Observation 4fe25be8-31ac-4e38-ad82-4fd2d5c1b3ae · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Scaling laws for fact memorization of large language models,
Reference 7
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Observation 35705598-4f76-4ce6-ac1d-051775e20669 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Scaling Laws for Neural Language Models
Reference 8
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Observation 1a9316e9-6113-4d7c-a747-ab3feb23201d · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Towards reasoning ability of small language models,
Reference 9
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Observation c0257854-b4dc-4c88-8146-db1f251a0f0f · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Why Language Models Hallucinate
Reference 10
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Observation db84c1f4-36ce-45a6-89a1-01fc69006180 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Human-written vs. ai- generated code: A large-scale study of defects, vulnerabilities, and complexity,
Reference 11
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Observation 18cc4b6a-9007-44bc-987d-c89d14803fb8 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Speed at the cost of quality: How cursor ai increases short-term velocity and long-term complexity in open-source projects,
Reference 12
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Observation 0914197e-d1f3-4758-9c54-5c67a28cf066 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
Reference 13
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Observation 5d363549-ae59-4752-9115-d574dc46c6c2 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Supercode: Sustainability per ai-driven co-design,
Reference 14
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Observation 89c13c2e-c33c-4303-ac43-6adc5ca194dc · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Lofar: The low-frequency array,
Reference 15
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Observation 911db56a-b3ca-4aa6-966a-2780847fcdf5 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Into the depths: Unveiling elais-n1 with LOFAR’s deepest sub-arcsecond wide- field images,
Reference 16
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Observation 1aea54fc-798b-4012-9997-177fddf6119b · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy The lofar correlator: Implementation and performance analysis,
Reference 17
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Observation 3b8d858f-fb15-4a36-9882-df3d8d9d2064 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Commodity compute-and data-transport system design in modern large-scale distributed radio telescopes,
Reference 18
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Observation b6b61f02-870e-4147-b7f1-a3dcf9609baa · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Lofar2.0 documentation
Reference 19
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Observation db47622d-2253-4b34-a1e7-8aaa002e62d8 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Analogue neuromorphic receiver signal processing for radio astronomy,
Reference 20
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Observation f44ba6d9-93b4-4b5c-b516-b67cb4079ed7 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy How hungry is ai? benchmarking energy, water, and carbon footprint of llm inference,
Reference 21
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Observation 432461a2-6c1f-40c3-834b-1164e38900d3 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Carbon Emissions and Large Neural Network Training
Reference 22
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Observation 845f6e99-5b06-4c41-abf1-a81952eb4ddf · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Making ai less’ thirsty’,
Reference 23
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Observation 1ec85fbd-16ee-4954-9bea-004941790c13 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Trends in ai inference energy consumption: Beyond the performance-vs-parameter laws of deep learning,
Reference 24
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Observation 43dd49c6-b9fa-436a-9ddf-12cb9da08ee0 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Quantifying the Carbon Emissions of Machine Learning
Reference 25
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Observation a79b32bd-f177-4e8a-a9e1-89818ca90b14 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Retrieval- augmented generation for knowledge-intensive nlp tasks,
Reference 26
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Observation 2657a868-f393-4517-8149-4dc7b0a1a7d2 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy How interpretable are reasoning explanations from prompting large language models?
Reference 27
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Observation 2be047fb-ddca-474b-a5d7-92afae69f94e · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Deep sub-arcsecond wide-field imaging of the Lockman Hole field at 144 MHz,
Reference 28
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Observation f61223d4-63e2-49ec-86d3-75056f7cc3db · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Astron receives C4.6 million to widen and sharpen lofar’s cosmic vision
Reference 29
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Observation c132fb8c-8a28-4654-b162-229aceefa988 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy astrocamp: A community benchmark and co-design framework for sustainable ska-scale radio imaging,
Reference 30
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Observation 5828262b-768f-4b7c-acc4-1cd212950c57 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Celloai: Leveraging large language models for hpc software development in high energy physics,
Reference 31
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Observation eeca7fee-466b-4158-af0e-7425945247e6 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy The Larger the Better? Improved LLM Code-Generation via Budget Reallocation
Reference 32
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Observation 166f0faf-3904-461e-95dc-c79d7c7742cf · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Reference 33
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Observation 91954690-8ac9-4f3a-ba7f-a79a461b9b77 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy CodeT: Code Generation with Generated Tests
Reference 34
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Observation 07b8fed7-8396-44b6-8d10-b1f49bde2f6d · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy LEVER: Learning to Verify Language-to-Code Generation with Execution
Reference 35
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Observation 1d79c683-2206-4f18-b73c-3e4d8d06e50d · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Metis: fast quality-aware rag systems with configuration adaptation,
Reference 36
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Observation 330c41ff-490d-45a5-93ff-2e6985e59c5b · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy ContextPilot: Fast Long-Context Inference via Context Reuse
Reference 37
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Observation c49d3982-8b64-497b-bff8-789e0f74b128 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches
Reference 38
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Observation 4db2055a-313f-4063-a6ad-50062baf2940 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Demystifying chains, trees, and graphs of thoughts,
Reference 39
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Observation e8ccf86a-3342-4971-9b15-a63f73721ceb · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Chain-of-thought prompting elicits reasoning in large language models,
Reference 40
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Observation ba2ec3e6-f3d1-49f2-a324-bea2a8cf95cc · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 41
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Observation 1694cf9a-7615-4bb6-8a1e-978aae294c34 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Tree of thoughts: Deliberate problem solving with large language models,
Reference 42
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Observation 664bcbc4-8357-4e78-ba16-75556ad21786 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning
Reference 43
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Observation cfb2e5da-9495-4ca1-9c15-7e3e48acfe26 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Graph of thoughts: Solving elaborate problems with large language models,
Reference 44
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Observation 87caf9c3-d9ba-43ce-9224-b503eb6294e2 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Everything of thoughts: Defying the law of penrose triangle for thought generation,
Reference 45
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Observation bd68f257-c7fc-4c36-8b30-58731acccfed · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Buffer of thoughts: Thought-augmented reasoning with large language models,
Reference 46
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Observation 6923d45f-42e9-411a-afc9-83a38ee1cd94 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy LightRAG: Simple and Fast Retrieval-Augmented Generation
Reference 47
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Observation 519bb0fe-4c33-46a7-bece-9bb072b55da4 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Reversal of thought: Enhancing large language models with preference-guided reverse rea- soning warm-up,
Reference 48
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Observation 8c572676-27b6-4429-8d09-0cc59d649cd4 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Combining large language models with static analyzers for code review generation,
Reference 49
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Observation 013c11a7-48d4-4508-89fc-bc02909f9d2f · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Static analysis as a feedback loop: Enhancing llm-generated code beyond correctness,
Reference 50
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Observation 17a70aec-1cd1-4bd1-bb12-882778a4f502 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Producing wrong data without doing anything obviously wrong!
Reference 51
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Observation 90c7169c-fedc-47ed-b04d-e2ec2d964bc9 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Unresolved cited work
Reference 52
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Observation 6b74d4de-326e-4fdb-8444-e6625f134e10 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Rapidly selecting good compiler optimizations using per- formance counters,
Reference 53
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Observation 2c3b17ee-8f79-47dd-928f-88fcb2d8082c · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Crosscodeeval: A diverse and multilingual benchmark for cross-file code completion,
Reference 54
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Observation 6e1e6c20-e381-4c96-ad04-263782f24ac8 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Langchain community
Reference 55
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Observation 90745d2b-2720-4804-9301-5ce8ea0ec1da · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy The Faiss library
Reference 56
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Observation 8e6318a1-4d47-4a14-b803-503c4f6d6824 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Qwen2. 5 technical report,
Reference 57
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Observation a47ef160-bc25-4441-9f4e-7735f12aad71 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Coz: Finding code that counts with causal profiling,
Reference 58
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Observation 7db8256f-8501-4e2f-a506-02d8d051f8f4 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Job-level Carbon and Water Footprint Estimation for HPC: Bias Assessment from Runtime to Full Life Cycle
Reference 59
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Observation d2ac86a6-b9a9-4135-b461-2f49aee5ff24 · outbound
Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Evaluating large language models trained on code,
Reference 60
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No inbound Pith citation observations are available.