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Counterfactual Debiasing for Fact Verification 579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models Unlike existing works, CLEVER is augmentation-free and mitigates biases on infer- ence stage In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information
Measuring Mathematical Problem Solving With the MATH Dataset Abstract: Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers To measure this ability in machine learning models, we introduce MATH, a new dataset of 12,500 challenging competition mathematics problems Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations
Weakly-Supervised Affordance Grounding Guided by Part-Level. . . In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object interaction images and egocentric
NetMoE: Accelerating MoE Training through Dynamic Sample Placement 2 Clever design: reformulating the ILP to a weighted bipartite matching assignment problem and using Hungarian algorithm that has shorter solving time than communication time (so we can have actual speedup)
DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION - OpenReview Abstract: Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks In this paper we propose a new model architecture DeBERTa (Decoding-enhanced BERT with disentangled attention) that improves the BERT and RoBERTa models using two novel techniques The first is the disentangled attention mechanism, where
LLaVA-OneVision: Easy Visual Task Transfer | OpenReview We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the LLaVA-NeXT blog series Our