1 citations · 1 across the 10 of their papers we have counts for
11 papers
PhantomEnvironments: Training LLM Agents in Fictional Worlds
Anmol Kabra, Swathi Saravana Selvam, Albert Gong +5
Training LLM agents with reinforcement learning (RL) is bottlenecked by environments, which must provide verifiable rewards, support long-horizon interaction, and scale cheaply. Ex…
ORCA-bench: How Ready Are Language Model Agents for Oncall?
Albert Gong, Kyuseong Choi, Abhineet Agarwal +5
Large language models can write, patch, and search code, but oncall root cause analysis (RCA) demands something different: reasoning over noisy metrics, logs, traces, and source co…
Express Language Modeling
Albert Gong, Annabelle Michael Carrell, Raaz Dwivedi +1
We introduce a new tool, Express, for converting a non-causal attention approximation into a causal approximation with matching approximation guarantees. When combined with the sta…
Learning from Synthetic Data Improves Multi-hop Reasoning
Anmol Kabra, Yilun Yin, Albert Gong +6
Reinforcement Learning (RL) has been shown to significantly boost reasoning capabilities of large language models (LLMs) in math, coding, and multi-hop reasoning tasks. However, RL…
Electron-affinity difference distributions as an organizing principle for superconductivity, enabling the discovery of PtPbBi
Omri Lesser, Yanjun Liu, Natalie Maus +11
Predicting the superconducting transition temperature () from crystal structure and composition remains a central challenge in condensed-matter physics, reflecting the absence…
-CoT: Prolog-Initialized Chain-of-Thought Prompting for Multi-Hop Question-Answering
Chao Wan, Albert Gong, Mihir Mishra +3
Chain-of-Thought (CoT) prompting significantly enhances large language models' (LLMs) problem-solving capabilities, but still struggles with complex multi-hop questions, often fall…
N: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara +8
Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretical guarantees, including entry-w…
PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation
Albert Gong, Kamilė Stankevičiūtė, Chao Wan +6
High-quality benchmarks are essential for evaluating reasoning and retrieval capabilities of large language models (LLMs). However, curating datasets for this purpose is not a perm…
Low-Rank Thinning
Annabelle Michael Carrell, Albert Gong, Abhishek Shetty +2
The goal in thinning is to summarize a dataset using a small set of representative points. Remarkably, sub-Gaussian thinning algorithms like Kernel Halving and Compress can match t…
Supervised Kernel Thinning
Albert Gong, Kyuseong Choi, Raaz Dwivedi
The kernel thinning algorithm of Dwivedi & Mackey (2024) provides a better-than-i.i.d. compression of a generic set of points. By generating high-fidelity coresets of size signific…
Virtual CNN Branching: Efficient Feature Ensemble for Person Re-Identification
Albert Gong, Qiang Qiu, Guillermo Sapiro
In this paper we introduce an ensemble method for convolutional neural network (CNN), called "virtual branching," which can be implemented with nearly no additional parameters and…