Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2305.14516.
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
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, observed 2026-08-07T04:57:52.524155Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 5742a451-3951-488f-91f2-8f39680442a4 · inbound
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 115
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a503df21-1da7-458e-a01b-36c623d3d75c · inbound
Mycroft: Tracing Dependencies in Collective Communication Towards Reliable LLM Training Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 62
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f67695b0-17db-4c65-bc77-47ce67c7d415 · inbound
Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 57
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d17306f9-a22a-45a8-9eb1-7457d5612c3e · inbound
Opus: Photonic Rail-Optimized Fabric in ML Datacenters Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 77
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa326a8b-2a91-4313-848a-838370cc37d1 · inbound
Evaluating Cross-Architecture Performance Modeling of Distributed ML Workloads Using StableHLO Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 21398eeb-2451-4739-b3a1-e07a67cf7fb5 · inbound
Flint: Compiler Enabled Cluster-Free Design Space Exploration for Distributed ML Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 03c6736c-b573-4cf7-838e-aa6643a594df · inbound
MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 95
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 20652270-ea7e-4597-90a3-a9c580bff346 · inbound
MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 95
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7cfe14ba-8336-454d-833b-356017295caa · inbound
A Few GPUs, A Whole Lotta Scale: Faithful LLM Training Emulation with PrismLLM Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 547ad9ef-cb57-4942-b779-06f65de0dec8 · inbound
StageFrontier: Synchronization-Aware Stage Accounting for Distributed ML Training Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 22f94c45-ade9-442b-9b97-4c2f76ad1256 · inbound
StageFrontier: Synchronization-Aware Stage Accounting for Distributed ML Training Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 76e6fcc5-64ff-42c5-9537-79a55f01d003 · inbound
ASTRA-sim 3.0: Next-Level Distributed Machine Learning Simulations via High-Fidelity GPU and Infrastructure Modeling Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 25f95449-47b7-4b0d-8d31-adca7af6606b · inbound
Simulating Unified Tensor Resharding in heterogeneous AI systems Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 57
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation af68a08f-4f2c-4a15-a81f-2030d5b3fab6 · inbound
MoX: Efficient MoE Routing on Direct-Connect Topologies Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.