29 citations · 50 across the 7 of their papers we have counts for
7 papers
Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale
Tianyue Ou, Frank F. Xu, Aman Madaan +7
LLMs can now act as autonomous agents that interact with digital environments and complete specific objectives (e.g., arranging an online meeting). However, accuracy is still far f…
BASS: Batched Attention-optimized Speculative Sampling
Haifeng Qian, Sujan Kumar Gonugondla, Sungsoo Ha +6
Speculative decoding has emerged as a powerful method to improve latency and throughput in hosting large language models. However, most existing implementations focus on generating…
Bifurcated Attention: Accelerating Massively Parallel Decoding with Shared Prefixes in LLMs
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda +10
This study introduces bifurcated attention, a method designed to enhance language model inference in shared-context batch decoding scenarios. Our approach addresses the challenge o…
A Static Evaluation of Code Completion by Large Language Models
Hantian Ding, Varun Kumar, Yuchen Tian +9
Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to evaluate…
Multi-lingual Evaluation of Code Generation Models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang +22
We present new benchmarks on evaluation code generation models: MBXP and Multilingual HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are generated…
Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding
Jun Wang, Patrick Ng, Alexander Hanbo Li +5
Most recent research on Text-to-SQL semantic parsing relies on either parser itself or simple heuristic based approach to understand natural language query (NLQ). When synthesizing…
Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval
Uri Alon, Frank F. Xu, Junxian He +3
Retrieval-based language models (R-LM) model the probability of natural language text by combining a standard language model (LM) with examples retrieved from an external datastore…