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Paper Citation Record · LEDGER

Learning to Decode Collaboratively with Multiple Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2403.03870.

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

pith.paper-citation-record.v1
2403.03870 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:11:44.627016Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T18:48:20.393663Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b4012ad1-5d85-4e2c-9d01-0df1bc3e09c4 · inbound

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning cites this paper.

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning Learning to Decode Collaboratively with Multiple Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:48:20.396667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-23T18:46:08.566035Z digest=sha256:61c07c88a4ad7534d5cf7fdff4c2347f93a856331a5a3e9a87a88047bd789bb0

Observation e738b2c6-01bb-42f5-99ca-b0dbfa6622b1 · inbound

Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding cites this paper.

Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding Learning to Decode Collaboratively with Multiple Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T11:11:44.627016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:11:44.627016Z digest=sha256:71921f89332cb70d025038265052eeb1deef142385f68e748c4064a38aadb4ad

Observation bb353af5-3cf3-466e-8c95-3b4dac7ae297 · inbound

Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations cites this paper.

Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations Learning to Decode Collaboratively with Multiple Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T13:07:50.661630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:07:50.661630Z digest=sha256:2939a9f299991394715fea6a2899f7fb245c7c1482915649a3e78d32ccff0e33

Observation 92e8a7bb-c1f2-4b85-977f-36d960b88dfc · inbound

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding cites this paper.

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding Learning to Decode Collaboratively with Multiple Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:18.590507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:52:18.590507Z digest=sha256:334952896975341adb2e213dcfffdb3143b348bf16b91b805cc965c3096d5466

Observation e645b681-f8d5-4868-9005-3bcffac7dec8 · inbound

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration Learning to Decode Collaboratively with Multiple Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T21:16:14.673666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:16:14.673666Z digest=sha256:f1876ce7eed8a16dc2bb0bde983787d01d3131c1350a477d4cba4213a6611349

Observation c0a8c4d2-2fc9-46c6-922a-346fe07c2df7 · inbound

Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units cites this paper.

Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units Learning to Decode Collaboratively with Multiple Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-05T16:18:47.253931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:18:47.253931Z digest=sha256:18966b86d7a1f9cfa37dbeabe1c8ca2f508419f44fd2d7d74851679fc31f751b

Observation a57438e5-8adf-41b2-a66c-fc8ac83177bc · inbound

PyroDash: Cost-Efficient Token-Level Small-Large Language Model Collaborative Inference cites this paper.

PyroDash: Cost-Efficient Token-Level Small-Large Language Model Collaborative Inference Learning to Decode Collaboratively with Multiple Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T10:14:14.517955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:14:14.517955Z digest=sha256:63ec6999a6432f40d4d8dc4a9a60476ff5bc8933b66ac0e83409c9daa2900c62

Observation 0edff86b-d0fd-4f43-b954-97d849ed9dd5 · inbound

Inference-Time Consensus for Mitigating Hidden Behaviors from LLM Fine-Tuning cites this paper.

Inference-Time Consensus for Mitigating Hidden Behaviors from LLM Fine-Tuning Learning to Decode Collaboratively with Multiple Language Models

Reference 1948

Resolution
unresolved
no resolver link, observed 2026-07-30T23:28:39.340462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T23:28:39.340462Z digest=sha256:5be5418c82ce7ca8e8de23bedcff16b029b8502996db6f13455d2318a146a87f