SRCH:EEE02C1A
How does the adaptive distinguishing selection mechanism in Cast a Wider Net affect pass@k scores and coverage
Abstract
Abstract: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More i
Research Question
How does the adaptive distinguishing selection mechanism in Cast a Wider Net affect pass@k scores and coverage on the MathVista code subset compared to standard independent sampling with self-consistency decoding?
Verification Level
| Paper level | L2, Source-grounded claims | |
| Source-grounded claims | 5 | |
| Claim record source | not publicly specified |
Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.
Quality Tier
| Tier | DOI grade | |
| Basis | Review score and verified-claim count meet DOI-grade public quality thresholds. |
Descriptive public triage only; this tier does not alter current publication or DOI behavior.
Quality Dimensions
| Evidence strength | MEDIUM | |
| Citation grounding | MEDIUM | |
| Uncertainty disclosure | MEDIUM | |
| Reproducibility status | HIGH |
Automated triage signals derived from public fields; not human peer review or independent validation.
Correction Record
| Status | CURRENT |
| Correction count | 0 |
| Manifest contract | paper-manifest-v1.1 |
| Correction contract | correction-record-v1 |
Public corrections are additive records. Current status does not claim the synthesis is error-free.
Provenance
| Publisher | Assignee Research |
| Public provenance | L4, External archival record |
| Report artifact | Available |
| External record | Registered |
| Claim lineage | 5 aggregate source-grounded claims |
| Review method | Automated multi-reviewer assessment |
| Quality guide | How to read scores, claims, manifests, and evidence links |
| Provenance contract | source-provenance-v1 |
| Note | Machine-generated synthesis of existing literature. Not primary research. |