67 citations · 86 across the 12 of their papers we have counts for
8 papers · 1 filter
ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research
Sohyeon Kim, Yoonho Lee, Bo Liu +11
What makes great scientists great? Even as AI systems start to make progress on open problems, scientists remain far ahead of them at sensing which prior idea, buried in an ever-gr…
PR-Smoother: Simulator-Preserving Non-Gaussian Smoothing for Data Assimilation
Yuta Tarumi
Many physical data assimilation (DA) workflows require smoothing methods that represent non-Gaussian posteriors over physical state variables, scale to high-dimensional simulators,…
Crypto Accounting Bench: Evaluating Frontier and Open-Weight Models on Crypto-Asset Accounting Tasks
Kareem Khattab, Omar Khattab, Mohamed Ibrahem
We introduce Crypto Accounting Bench (CAB), a benchmark for assessing whether frontier and open-weight language models can reconstruct the complete journal entry that an organizati…
Carnot: Interpretable, Interactive, and Optimized Execution of Deep Research Queries
Matthew Russo, Yash Agarwal, Tianyu Li +5
Enterprises increasingly seek to query data lakes using natural language via AI-driven tools like semantic operators or deep research agents. However, the latter operates as an opa…
OBLIQ-Bench: Exposing Overlooked Bottlenecks in Modern Retrievers with Latent and Implicit Queries
Diane Tchuindjo, Devavrat Shah, Omar Khattab
Retrieval benchmarks are increasingly saturating, but we argue that efficient search is far from a solved problem. We identify a class of queries we call oblique, which seek docume…
Vector Policy Optimization: Training for Diversity Improves Test-Time Search
Ryan Bahlous-Boldi, Isha Puri, Idan Shenfeld +6
Language models must now generalize out of the box to novel environments and work inside inference-scaling search procedures, such as AlphaEvolve, that select rollouts with a varie…
PEEK: Context Map as an Orientation Cache for Long-Context LLM Agents
Zhuohan Gu, Qizheng Zhang, Omar Khattab +1
Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across invocations, existing approach…
Meta-Harness: End-to-End Optimization of Model Harnesses
Yoonho Lee, Roshen Nair, Qizheng Zhang +3
The performance of large language model (LLM) systems depends not only on model weights, but also on their harness: the code that determines what information to store, retrieve, an…