3 citations · 6 across the 10 of their papers we have counts for
11 papers
A Phenomenology of Neural Geometry in Vision-Language-Action Models
Mozes Jacobs, Aiden Swann, Mathilde Papillon +16
Robotic manipulation is inherently geometric, but what shape does the world take inside the policy that performs it? Prior work on vision-language-action (VLA) policies establishes…
Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal
Leon Bergen, Usha Bhalla, Sidharth Baskaran +14
Language-model post-training is the main stage at which model behavior is shaped, yet it still largely involves optimization of scalar rewards that summarize diverse desiderata. Th…
CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction
Jianyou Wang, Youze Zheng, Longtian Bao +11
Scientists have long sought to accurately predict outcomes of real-world events before they happen. Can AI systems do so more reliably? We study this question through clinical tria…
Quiet Feature Learning in Algorithmic Tasks
Prudhviraj Naidu, Zixian Wang, Leon Bergen +1
We train Transformer-based language models on ten foundational algorithmic tasks and observe pronounced phase transitions in their loss curves that deviate from established power-l…
EvidenceBench: A Benchmark for Extracting Evidence from Biomedical Papers
Jianyou Wang, Weili Cao, Kaicheng Wang +13
We study the task of automatically finding evidence relevant to hypotheses in biomedical papers. Finding relevant evidence is an important step when researchers investigate scienti…
Single-Pass Document Scanning for Question Answering
Weili Cao, Jianyou Wang, Youze Zheng +5
Handling extremely large documents for question answering is challenging: chunk-based embedding methods often lose track of important global context, while full-context transformer…
Measuring Risk of Bias in Biomedical Reports: The RoBBR Benchmark
Jianyou Wang, Weili Cao, Longtian Bao +6
Systems that answer questions by reviewing the scientific literature are becoming increasingly feasible. To draw reliable conclusions, these systems should take into account the qu…
Dissociation of Faithful and Unfaithful Reasoning in LLMs
Evelyn Yee, Alice Li, Chenyu Tang +3
Large language models (LLMs) often improve their performance in downstream tasks when they generate Chain of Thought reasoning text before producing an answer. We investigate how L…
BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives
Xiaoyue Wang, Jianyou Wang, Weili Cao +3
We present the Benchmark of Information Retrieval (IR) tasks with Complex Objectives (BIRCO). BIRCO evaluates the ability of IR systems to retrieve documents given multi-faceted us…
IR2: Information Regularization for Information Retrieval
Jianyou Wang, Kaicheng Wang, Xiaoyue Wang +3
Effective information retrieval (IR) in settings with limited training data, particularly for complex queries, remains a challenging task. This paper introduces IR2, Information Re…
DORIS-MAE: Scientific Document Retrieval using Multi-level Aspect-based Queries
Jianyou Wang, Kaicheng Wang, Xiaoyue Wang +3
In scientific research, the ability to effectively retrieve relevant documents based on complex, multifaceted queries is critical. Existing evaluation datasets for this task are li…