Evidence assessment
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- Source
- url:https://arxiv.org/abs/1810.04805
- Pages
- 16
Assessment outcome
Insufficient evidence to score confidently
Assessment confidence: LimitedPaper type: Uncertain or General
Why this score
Insufficient evidence to score confidently
Missing information
- Required stage claims did not produce usable output.
- Required stage evidence did not produce usable output.
- Required stage methodology did not produce usable output.
- Source record kind struct provided 0 usable records; required minimum: 1.
- Source record kind claim provided 0 usable records; required minimum: 1.
- Source record kind evidence provided 0 usable records; required minimum: 1.
- Source record kind method provided 0 usable records; required minimum: 1.
- Major claim count was 0; required minimum: 1.
- No scored criterion was produced; at least one scored criterion was required.
- No scored dimension was produced; at least one scored dimension was required.
- Assessable configured dimension weight 0 was below 70% of applicable configured weight 1.00; 0.70 was required.
Dimensions and criteria
- Not assessable
Claim-evidence alignment
general.claim_evidence_alignment
Not assessable
- Configured weight
- 0.40
- Effective weight
- Not scored
Criteria
general_claim_evidence_alignment_support_coverage
- Status
- Not assessable
- Rating
- Not assessable
- Points
- Not scored
- Configured weight
- 0.50
- Effective weight
- Not scored
general_claim_evidence_alignment_scope_and_nature
- Status
- Not assessable
- Rating
- Not assessable
- Points
- Not scored
- Configured weight
Claim alignments
No claim alignments are available.
Within-paper comparisons
No within-paper comparisons are available.
Methodology
Methodology checklist
No methodology records were extracted.
Limitations
External competitiveness was not assessed.
Missing information
- Required stage claims did not produce usable output.
- Required stage evidence did not produce usable output.
- Required stage methodology did not produce usable output.
- Source record kind struct provided 0 usable records; required minimum: 1.
- Source record kind claim provided 0 usable records; required minimum: 1.
- Source record kind evidence provided 0 usable records; required minimum: 1.
- Source record kind method provided 0 usable records; required minimum: 1.
- Major claim count was 0; required minimum: 1.
- No scored criterion was produced; at least one scored criterion was required.
- No scored dimension was produced; at least one scored dimension was required.
- Assessable configured dimension weight 0 was below 70% of applicable configured weight 1.00; 0.70 was required.
Paper context
- problem_limitation_of_unidirectional_models
- The ma- jor limitation is that standard language models are unidirectional, and this limits the choice of archi- tectures that can be used during pre-training.
- section · page 1 · 1 Introduction
- proposed_approach_bert_masked_lm
- In this paper, we improve the fine-tuning based approaches by proposing BERT: Bidirectional Encoder Representations from Transformers. BERT alleviates the previously mentioned unidi- rectionality constraint by using a “masked lan- guage model” (MLM) pre-training objective, in- spired by the Cloze task (Taylor, 1953).
- section · page 1 · 1 Introduction
- key_contribution_bidirectional_pretraining
- • We demonstrate the importance of bidirectional pre-training for language representations. Un- like Radford et al. (2018), which uses unidirec- tional language models for pre-training, BERT uses masked language models to enable pre- trained deep bidirectional representations. This is also in contrast to Peters et al. (2018a), which uses a shallow concatenation of independently trained left-to-right and right-to-left LMs.
- section · page 2 · 1 Introduction
Evidence ledger
Evidence ledger
No source records are available.