Search Results for author:
Found 16 papers, 5 papers with code
Transforming LLMs into Cross-modal and Cross-lingual Retrieval Systems
Our multi-modal LLM-based retrieval system is capable of matching speech and text in 102 languages despite only training on 21 languages.
Characterizing Tradeoffs in Language Model Decoding with Informational Interpretations
We propose a theoretical framework for formulating language model decoder algorithms with dynamic programming and information theory.
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
Specifically, we introduce FreshQA, a novel dynamic QA benchmark encompassing a diverse range of question and answer types, including questions that require fast-changing world knowledge as well as questions with false premises that need to be debunked.
KL-Divergence Guided Temperature Sampling
One common approach to mitigate hallucinations is to provide source/grounding documents and the model is trained to produce predictions that bind to and are attributable to the provided source.
CoLT5: Faster Long-Range Transformers with Conditional Computation
Many natural language processing tasks benefit from long inputs, but processing long documents with Transformers is expensive -- not only due to quadratic attention complexity but also from applying feedforward and projection layers to every token.
Ranked #1 on
Long-range modeling
on SCROLLS
Knowledge Prompts: Injecting World Knowledge into Language Models through Soft Prompts
The resulting soft knowledge prompts (KPs) are task independent and work as an external memory of the LMs.
LongT5: Efficient Text-To-Text Transformer for Long Sequences
Recent work has shown that either (1) increasing the input length or (2) increasing model size can improve the performance of Transformer-based neural models.
Ranked #1 on
Text Summarization
on BigPatent
Multilingual Universal Sentence Encoder for Semantic Retrieval
We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures.
Hierarchical Document Encoder for Parallel Corpus Mining
We explore using multilingual document embeddings for nearest neighbor mining of parallel data.
Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model
A significant roadblock in multilingual neural language modeling is the lack of labeled non-English data.
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings.
Learning Semantic Textual Similarity from Conversations
We present a novel approach to learn representations for sentence-level semantic similarity using conversational data.
Universal Sentence Encoder
For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.
Ranked #2 on
Text Classification
on TREC-6
Conversational Response Selection
Semantic Textual Similarity
+7
Efficient Natural Language Response Suggestion for Smart Reply
This paper presents a computationally efficient machine-learned method for natural language response suggestion.
Conversational Contextual Cues: The Case of Personalization and History for Response Ranking
Unlike previous efforts, which focused on modeling messages and responses, we extend the modeling to long context and participant's history.
