Daniel Korat
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View article: Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies Open
Accelerating the inference of large language models (LLMs) is a critical challenge in generative AI. Speculative decoding (SD) methods offer substantial efficiency gains by generating multiple tokens using a single target forward pass. How…
View article: Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference Open
This paper introduces distributed speculative inference (DSI), a novel inference algorithm that is provably faster than speculative inference (SI) [leviathan2023, chen2023, miao2024, sun2025, timor2025] and standard autoregressive inferenc…
View article: Dynamic Speculation Lookahead Accelerates Speculative Decoding of Large Language Models
Dynamic Speculation Lookahead Accelerates Speculative Decoding of Large Language Models Open
Speculative decoding is commonly used for reducing the inference latency of large language models. Its effectiveness depends highly on the speculation lookahead (SL)-the number of tokens generated by the draft model at each iteration. In t…
View article: Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs Open
The extraction of aspect terms is a critical step in fine-grained sentiment\nanalysis of text. Existing approaches for this task have yielded impressive\nresults when the training and testing data are from the same domain. However,\nthese …
View article: Efficient Few-Shot Learning Without Prompts
Efficient Few-Shot Learning Without Prompts Open
Recent few-shot methods, such as parameter-efficient fine-tuning (PEFT) and pattern exploiting training (PET), have achieved impressive results in label-scarce settings. However, they are difficult to employ since they are subject to high …
View article: Opinion-based Relational Pivoting for Cross-domain Aspect Term Extraction
Opinion-based Relational Pivoting for Cross-domain Aspect Term Extraction Open
Domain adaptation methods often exploit domain-transferable input features, a.k.a. pivots. The task of Aspect and Opinion Term Extraction presents a special challenge for domain transfer: while opinion terms largely transfer across domains…
View article: InterpreT: An Interactive Visualization Tool for Interpreting Transformers
InterpreT: An Interactive Visualization Tool for Interpreting Transformers Open
Vasudev Lal, Arden Ma, Estelle Aflalo, Phillip Howard, Ana Simoes, Daniel Korat, Oren Pereg, Gadi Singer, Moshe Wasserblat. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System…
View article: 3D Neural Network for Lung Cancer Risk Prediction on CT Volumes
3D Neural Network for Lung Cancer Risk Prediction on CT Volumes Open
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer CT screening has been shown to reduce mortality by up to 40% and is now included in US screening guidelines. R…
View article: Syntactically Aware Cross-Domain Aspect and Opinion Terms Extraction
Syntactically Aware Cross-Domain Aspect and Opinion Terms Extraction Open
A fundamental task of fine-grained sentiment analysis is aspect and opinion terms extraction. Supervised-learning approaches have shown good results for this task; however, they fail to scale across domains where labeled data is lacking. N…
View article: ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System Open
We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction. The system is interpretable and user friendly and does not require labeled training data, hence can be rapidly and cost-effectively used across d…
View article: ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System Open
Oren Pereg, Daniel Korat, Moshe Wasserblat, Jonathan Mamou, Ido Dagan. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-…
View article: NLP Architect by Intel AI Lab
NLP Architect by Intel AI Lab Open
NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. Release v0.3 New Solution Topics and Trend Analy…
View article: Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow
Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow Open
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to end workflow for term set expansion. It en…
View article: Term Set Expansion based NLP Architect by Intel AI Lab
Term Set Expansion based NLP Architect by Intel AI Lab Open
We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily se…