72 citations · 228 across the 19 of their papers we have counts for
20 papers
S-EMBER: A Large-Scale Benchmark for Streaming Egocentric Memory Retrieval
Xiaodong Wang, Xuanyi Zhao, Pedro Rodriguez +7
As wearable devices enable continuous first-person recording, AI assistants must reason across long time horizons to recall past experiences-a capability known as episodic memory.…
Procedural Knowledge at Scale Improves Reasoning
Di Wu, Devendra Singh Sachan, Wen-tau Yih +1
Test-time scaling has emerged as an effective way to improve language models on challenging reasoning tasks. However, most existing methods treat each problem in isolation and do n…
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval
Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan +5
Recent advances in large language models (LLMs) have enabled autonomous agents with complex reasoning and task-fulfillment capabilities using a wide range of tools. However, effect…
Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?
Jinhyuk Lee, Anthony Chen, Zhuyun Dai +16
Long-context language models (LCLMs) have the potential to revolutionize our approach to tasks traditionally reliant on external tools like retrieval systems or databases. Leveragi…
Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions
Cuong Hoang, Devendra Sachan, Prashant Mathur +2
Several recent studies have reported dramatic performance improvements in neural machine translation (NMT) by augmenting translation at inference time with fuzzy-matches retrieved…
Improving Retrieval Augmented Neural Machine Translation by Controlling Source and Fuzzy-Match Interactions
Cuong Hoang, Devendra Sachan, Prashant Mathur +2
We explore zero-shot adaptation, where a general-domain model has access to customer or domain specific parallel data at inference time, but not during training. We build on the id…