Search Results for author: Ahmed Awadallah

Found 14 papers, 7 papers with code

Teaching Language Models to Hallucinate Less with Synthetic Tasks

no code implementations10 Oct 2023 Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Awadallah, Ece Kamar

We also find that optimizing the system message rather than the model weights can be critical; fine-tuning the entire model on the synthetic task can counterintuitively increase hallucination.

Abstractive Text Summarization Meeting Summarization +2

SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference

no code implementations5 Jul 2023 Luciano del Corro, Allie Del Giorno, Sahaj Agarwal, Bin Yu, Ahmed Awadallah, Subhabrata Mukherjee

While existing token-level early exit methods show promising results for online inference, they cannot be readily applied for batch inferencing and Key-Value caching.

Text Generation

Orca: Progressive Learning from Complex Explanation Traces of GPT-4

6 code implementations5 Jun 2023 Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, Ahmed Awadallah

To address these challenges, we develop Orca (We are working with our legal team to publicly release a diff of the model weights in accordance with LLaMA's release policy to be published at https://aka. ms/orca-lm), a 13-billion parameter model that learns to imitate the reasoning process of LFMs.

Imitation Learning Knowledge Distillation

ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels

1 code implementation24 Aug 2022 Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, Ahmed Awadallah

In this work, we propose a method to leverage weak/noisy labels (e. g., risk scores generated by machine rules for detecting malware) that are cheaper to obtain for anomaly detection.

Anomaly Detection

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy

1 code implementation CVPR 2022 Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang

However, a "head-to-toe assessment" regarding the extent of redundancy in ViTs, and how much we could gain by thoroughly mitigating such, has been absent for this field.

Uncertainty-aware Self-training for Few-shot Text Classification

no code implementations NeurIPS 2020 Subhabrata Mukherjee, Ahmed Awadallah

Recent success of pre-trained language models crucially hinges on fine-tuning them on large amounts of labeled data for the downstream task, that are typically expensive to acquire or difficult to access for many applications.

Few-Shot Text Classification General Classification +2

Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching

no code implementations22 Apr 2018 Xiao Yang, Miaosen Wang, Wei Wang, Madian Khabsa, Ahmed Awadallah, Daniel Kifer, C. Lee Giles

We frame this task as a binary (relevant/irrelevant) classification problem, and present an adversarial training framework to alleviate label imbalance issue.

Answer Selection General Classification

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