4 citations · 5 across the 7 of their papers we have counts for
7 papers
Explaining Attention with Program Synthesis
Amiri Hayes, Belinda Z Li, Jacob Andreas
A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descriptions. In this paper, we propose an ap…
VISUALSKILL: Multimodal Skills for Computer-Use Agents
Ziyan Jiang, Li An, Yujian Liu +5
Computer-use agents (CUAs) approach human-level performance on standardised benchmarks but still struggle on long-horizon tasks and unseen software. Existing skill libraries addres…
Self-CTRL: Self-Consistency Training with Reinforcement Learning
Itamar Pres, Laura Ruis, Melat Ghebreselassie +2
Language models (LMs) that faithfully describe their own behavior can more easily be audited, understood, and trusted by users. This paper describes Self-Consistency Training with…
ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning
Bairu Hou, Yang Zhang, Jiabao Ji +4
We present ThinkPrune, a simple yet effective method for pruning the thinking length for long-thinking LLMs, which has been found to often produce inefficient and redundant thinkin…
A Hitchhiker's Guide to Scaling Law Estimation
Leshem Choshen, Yang Zhang, Jacob Andreas
Scaling laws predict the loss of a target machine learning model by extrapolating from easier-to-train models with fewer parameters or smaller training sets. This provides an effic…
A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation
Bairu Hou, Yang Zhang, Jacob Andreas +1
This paper focuses on the task of hallucination detection, which aims to determine the truthfulness of LLM-generated statements. To address this problem, a popular class of methods…
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou, Yujian Liu, Kaizhi Qian +3
Uncertainty decomposition refers to the task of decomposing the total uncertainty of a predictive model into aleatoric (data) uncertainty, resulting from inherent randomness in the…