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France-CS-CS Azienda Directories
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Azienda News:
- Counterfactual Debiasing for Fact Verification - OpenReview
016 namely CLEVER, which is augmentation-free 017 and mitigates biases on the inference stage 018 Specifically, we train a claim-evidence fusion 019 model and a claim-only model independently 020 Then, we obtain the final prediction via sub-021 tracting output of the claim-only model from 022 output of the claim-evidence fusion model,
- Measuring Mathematical Problem Solving With the MATH Dataset
To find the limits of Transformers, we collected 12,500 math problems While a three-time IMO gold medalist got 90%, GPT-3 models got ~5%, with accuracy increasing slowly
- 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 object images without dense labels
- Large Language Models are Human-Level Prompt Engineers
We propose an algorithm for automatic instruction generation and selection for large language models with human level performance
- Reasoning of Large Language Models over Knowledge Graphs with. . .
While large language models (LLMs) have made significant progress in processing and reasoning over knowledge graphs, current methods suffer from a high non-retrieval rate
- Thieves on Sesame Street! Model Extraction of BERT-based APIs
Finally, we study two defense strategies against model extraction—membership classification and API watermarking—which while successful against some adversaries can also be circumvented by more clever ones
- MIND over Body: Adaptive Thinking using Dynamic Computation
Keywords: Interpretability, Fixed points, Dynamic routing, Dynamic input processing, Deep Learning Framework
- DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION
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
- Diffusion Generative Modeling for Spatially Resolved Gene. . .
Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by systematically connecting cell morphology depicted in Hematoxylin and eosin (H\ E) stained histology images to spatially resolved gene expressions
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