146 citations · 656 across the 31 of their papers we have counts for
31 papers
Olmo 3
Team Olmo, :, Allyson Ettinger +66
We introduce Olmo 3, a family of state-of-the-art, fully-open language models at the 7B and 32B parameter scales. Olmo 3 model construction targets long-context reasoning, function…
CodeRAG-Bench: Can Retrieval Augment Code Generation?
Zora Zhiruo Wang, Akari Asai, Xinyan Velocity Yu +4
While language models (LMs) have proven remarkably adept at generating code, many programs are challenging for LMs to generate using their parametric knowledge alone. Providing ext…
Reliable, Adaptable, and Attributable Language Models with Retrieval
Akari Asai, Zexuan Zhong, Danqi Chen +4
Parametric language models (LMs), which are trained on vast amounts of web data, exhibit remarkable flexibility and capability. However, they still face practical challenges such a…
Fine-grained Hallucination Detection and Editing for Language Models
Abhika Mishra, Akari Asai, Vidhisha Balachandran +4
Large language models (LMs) are prone to generate factual errors, which are often called hallucinations. In this paper, we introduce a comprehensive taxonomy of hallucinations and…
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Akari Asai, Zeqiu Wu, Yizhong Wang +2
Despite their remarkable capabilities, large language models (LLMs) often produce responses containing factual inaccuracies due to their sole reliance on the parametric knowledge t…
BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer
Akari Asai, Sneha Kudugunta, Xinyan Velocity Yu +6
Despite remarkable advancements in few-shot generalization in natural language processing, most models are developed and evaluated primarily in English. To facilitate research on f…
xPQA: Cross-Lingual Product Question Answering across 12 Languages
Xiaoyu Shen, Akari Asai, Bill Byrne +1
Product Question Answering (PQA) systems are key in e-commerce applications to provide responses to customers' questions as they shop for products. While existing work on PQA focus…
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo, Tajuddeen R. Gwadabe, Clara E. Rivera +49
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingu…
TaskWeb: Selecting Better Source Tasks for Multi-task NLP
Joongwon Kim, Akari Asai, Gabriel Ilharco +1
Recent work in NLP has shown promising results in training models on large amounts of tasks to achieve better generalization. However, it is not well-understood how tasks are relat…
How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval
Sheng-Chieh Lin, Akari Asai, Minghan Li +5
Various techniques have been developed in recent years to improve dense retrieval (DR), such as unsupervised contrastive learning and pseudo-query generation. Existing DRs, however…
Task-aware Retrieval with Instructions
Akari Asai, Timo Schick, Patrick Lewis +5
We study the problem of retrieval with instructions, where users of a retrieval system explicitly describe their intent along with their queries. We aim to develop a general-purpos…
When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories
Alex Mallen, Akari Asai, Victor Zhong +3
Despite their impressive performance on diverse tasks, large language models (LMs) still struggle with tasks requiring rich world knowledge, implying the limitations of relying sol…
Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources
Xinyan Velocity Yu, Akari Asai, Trina Chatterjee +2
While the NLP community is generally aware of resource disparities among languages, we lack research that quantifies the extent and types of such disparity. Prior surveys estimatin…
MIA 2022 Shared Task: Evaluating Cross-lingual Open-Retrieval Question Answering for 16 Diverse Languages
Akari Asai, Shayne Longpre, Jungo Kasai +6
We present the results of the Workshop on Multilingual Information Access (MIA) 2022 Shared Task, evaluating cross-lingual open-retrieval question answering (QA) systems in 16 typo…
RealTime QA: What's the Answer Right Now?
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi +7
We introduce REALTIME QA, a dynamic question answering (QA) platform that announces questions and evaluates systems on a regular basis (weekly in this version). REALTIME QA inquire…
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts
Akari Asai, Mohammadreza Salehi, Matthew E. Peters +1
This work introduces a new multi-task, parameter-efficient language model (LM) tuning method that learns to transfer knowledge across different tasks via a mixture of soft prompts-…
Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks
Akari Asai, Matt Gardner, Hannaneh Hajishirzi
Retrieval-augmented generation models have shown state-of-the-art performance across many knowledge-intensive NLP tasks such as open question answering and fact verification. These…
One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval
Akari Asai, Xinyan Yu, Jungo Kasai +1
We present Cross-lingual Open-Retrieval Answer Generation (CORA), the first unified many-to-many question answering (QA) model that can answer questions across many languages, even…
Efficient Passage Retrieval with Hashing for Open-domain Question Answering
Ikuya Yamada, Akari Asai, Hannaneh Hajishirzi
Most state-of-the-art open-domain question answering systems use a neural retrieval model to encode passages into continuous vectors and extract them from a knowledge source. Howev…
MultiModalQA: Complex Question Answering over Text, Tables and Images
Alon Talmor, Ori Yoran, Amnon Catav +6
When answering complex questions, people can seamlessly combine information from visual, textual and tabular sources. While interest in models that reason over multiple pieces of e…
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals
Takumi Kawashima, Qing Yu, Akari Asai +2
We propose a new optimization framework for aleatoric uncertainty estimation in regression problems. Existing methods can quantify the error in the target estimation, but they tend…
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
Ikuya Yamada, Akari Asai, Hiroyuki Shindo +2
Entity representations are useful in natural language tasks involving entities. In this paper, we propose new pretrained contextualized representations of words and entities based…
Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval
Akari Asai, Eunsol Choi
Recent pretrained language models "solved" many reading comprehension benchmarks, where questions are written with access to the evidence document. However, datasets containing inf…
XOR QA: Cross-lingual Open-Retrieval Question Answering
Akari Asai, Jungo Kasai, Jonathan H. Clark +3
Multilingual question answering tasks typically assume answers exist in the same language as the question. Yet in practice, many languages face both information scarcity -- where l…