1 citations · 2 across the 8 of their papers we have counts for
8 papers
Personagram: Bridging Personas and Product Design for Creative Ideation with Multimodal LLMs
Taewook Kim, Matthew K. Hong, Yan-Ying Chen +5
Product designers often begin their design process with handcrafted personas. While personas are intended to ground design decisions in consumer preferences, they often fall short…
DVGBench: Implicit-to-Explicit Visual Grounding Benchmark in UAV Imagery with Large Vision-Language Models
Yue Zhou, Jue Chen, Zilun Zhang +10
Remote sensing (RS) large vision-language models (LVLMs) have shown strong promise across visual grounding (VG) tasks. However, existing RS VG datasets predominantly rely on explic…
A State-of-the-Art SQL Reasoning Model using RLVR
Alnur Ali, Ashutosh Baheti, Jonathan Chang +13
Developing custom reasoning models via Reinforcement Learning (RL) that can incorporate organization-specific knowledge has great potential to address problems faced by enterprise…
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice
Jonathan Li, Rohan Bhambhoria, Samuel Dahan +1
Generative AI models, such as the GPT and Llama series, have significant potential to assist laypeople in answering legal questions. However, little prior work focuses on the data…
Evaluating AI for Law: Bridging the Gap with Open-Source Solutions
Rohan Bhambhoria, Samuel Dahan, Jonathan Li +1
This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It s…
Prefix Propagation: Parameter-Efficient Tuning for Long Sequences
Jonathan Li, Will Aitken, Rohan Bhambhoria +1
Parameter-efficient tuning aims to mitigate the large memory requirements of adapting pretrained language models for downstream tasks. For example, one popular method, prefix-tunin…
Parameter-Efficient Legal Domain Adaptation
Jonathan Li, Rohan Bhambhoria, Xiaodan Zhu
Seeking legal advice is often expensive. Recent advancements in machine learning for solving complex problems can be leveraged to help make legal services more accessible to the pu…