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Paper Citation Record · LEDGER

Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.08901.

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

pith.paper-citation-record.v1
2312.08901 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:59:38.658210Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T02:39:33.301814Z

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 35b09331-5dab-4681-97d8-2655f4f3b3d5 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:39:33.303834Z

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=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:142070bfe0d7df6f05b2a9fe1fc445270c36ffafcbb8f97513933180f7d0eb5a

Observation a8723607-69db-48f5-8958-eb1e23352131 · inbound

CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models cites this paper.

CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:59:38.658210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:59:38.658210Z digest=sha256:ee30a94c24754996bc3262c167d9a29da1269b40d5b7db3715aae77b961c0cbc

Observation c1c4ea3d-8a90-427e-90a0-41bd95cf66ad · inbound

Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence cites this paper.

Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:06.836586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:06.836586Z digest=sha256:7e3936baf42d74f23ad121dcbd48f0c0e12b5428ac23d4c02128b41b5aa915d1

Observation c295cae3-eb0a-489c-8b56-786356d1ea2b · inbound

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation cites this paper.

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:49.722603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:49.722603Z digest=sha256:c4c2f4efd93a1b842575d7711c5abd3fe717589ea8fe10195696c0761246568d

Observation b8647e7b-43ac-4855-b118-734e16bc18d0 · inbound

LLMs with in-context learning for Algorithmic Theoretical Physics cites this paper.

LLMs with in-context learning for Algorithmic Theoretical Physics Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:31:25.727713Z

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=pdf_text observed=2026-05-12T01:00:44.364356Z digest=sha256:f99f862f4f3d7d37cbec3cdf96c514e5a46b866522e9985d02c35925976f0c79