14 citations · 22 across the 9 of their papers we have counts for
10 papers
How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs
Yapei Chang, Kyle Lo, Mohit Iyyer +1
Generating step-by-step "how-to" procedures is a key LLM capability: how-to advice is commonly requested in chatbots, and step-by-step planning is critical for reasoning over compl…
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…
BLEUBERI: BLEU is a surprisingly effective reward for instruction following
Yapei Chang, Yekyung Kim, Michael Krumdick +4
Reward models are central to aligning LLMs with human preferences, but they are costly to train, requiring large-scale human-labeled preference data and powerful pretrained LLM bac…
BEARCUBS: A benchmark for computer-using web agents
Yixiao Song, Katherine Thai, Chau Minh Pham +3
Modern web agents possess computer use abilities that allow them to interact with webpages by sending commands to a virtual keyboard and mouse. While such agents have considerable…
CLIPPER: Compression enables long-context synthetic data generation
Chau Minh Pham, Yapei Chang, Mohit Iyyer
LLM developers are increasingly reliant on synthetic data, but generating high-quality data for complex long-context reasoning tasks remains challenging. We introduce CLIPPER, a co…
PostMark: A Robust Blackbox Watermark for Large Language Models
Yapei Chang, Kalpesh Krishna, Amir Houmansadr +2
The most effective techniques to detect LLM-generated text rely on inserting a detectable signature -- or watermark -- during the model's decoding process. Most existing watermarki…
FABLES: Evaluating faithfulness and content selection in book-length summarization
Yekyung Kim, Yapei Chang, Marzena Karpinska +5
While long-context large language models (LLMs) can technically summarize book-length documents (>100K tokens), the length and complexity of the documents have so far prohibited ev…
BooookScore: A systematic exploration of book-length summarization in the era of LLMs
Yapei Chang, Kyle Lo, Tanya Goyal +1
Summarizing book-length documents (>100K tokens) that exceed the context window size of large language models (LLMs) requires first breaking the input document into smaller chunks…
RankGen: Improving Text Generation with Large Ranking Models
Kalpesh Krishna, Yapei Chang, John Wieting +1
Given an input sequence (or prefix), modern language models often assign high probabilities to output sequences that are repetitive, incoherent, or irrelevant to the prefix; as suc…
RELIC: Retrieving Evidence for Literary Claims
Katherine Thai, Yapei Chang, Kalpesh Krishna +1
Humanities scholars commonly provide evidence for claims that they make about a work of literature (e.g., a novel) in the form of quotations from the work. We collect a large-scale…