3 citations · 17 across the 25 of their papers we have counts for
10 papers · 1 filter
CARE: Turning LLMs Into Causal Reasoning Expert
Juncheng Dong, Yiling Liu, Ahmed Aloui +2
Large language models (LLMs) have recently demonstrated impressive capabilities across a range of reasoning and generation tasks. However, research studies have shown that LLMs lac…
Synergizing Deconfounding and Temporal Generalization For Time-series Counterfactual Outcome Estimation
Yiling Liu, Juncheng Dong, Chen Fu +4
Estimating counterfactual outcomes from time-series observations is crucial for effective decision-making, e.g. when to administer a life-saving treatment, yet remains significantl…
Neuro-Logic Lifelong Learning
Bowen He, Xiaoan Xu, Alper Kamil Bozkurt +2
Solving Inductive Logic Programming (ILP) problems with neural networks is a key challenge in Neural-Symbolic Ar- tificial Intelligence (AI). While most research has focused on des…
STARK: Strategic Team of Agents for Refining Kernels
Juncheng Dong, Yang Yang, Tao Liu +5
The efficiency of GPU kernels is central to the progress of modern AI, yet optimizing them remains a difficult and labor-intensive task due to complex interactions between memory h…
PASTA: A Unified Framework for Offline Assortment Learning
Juncheng Dong, Weibin Mo, Zhengling Qi +3
We study a broad class of assortment optimization problems in an offline and data-driven setting. In such problems, a firm lacks prior knowledge of the underlying choice model, and…
Conditional Average Treatment Effect Estimation Under Hidden Confounders
Ahmed Aloui, Juncheng Dong, Ali Hasan +1
One of the major challenges in estimating conditional potential outcomes and conditional average treatment effects (CATE) is the presence of hidden confounders. Since testing for h…
Boosting In-Context Learning in LLMs Through the Lens of Classical Supervised Learning
Korel Gundem, Juncheng Dong, Dennis Zhang +2
In-Context Learning (ICL) allows Large Language Models (LLMs) to adapt to new tasks with just a few examples, but their predictions often suffer from systematic biases, leading to…
Teleportation With Null Space Gradient Projection for Optimization Acceleration
Zihao Wu, Juncheng Dong, Ahmed Aloui +1
Optimization techniques have become increasingly critical due to the ever-growing model complexity and data scale. In particular, teleportation has emerged as a promising approach,…
S2TX: Cross-Attention Multi-Scale State-Space Transformer for Time Series Forecasting
Zihao Wu, Juncheng Dong, Haoming Yang +1
Time series forecasting has recently achieved significant progress with multi-scale models to address the heterogeneity between long and short range patterns. Despite their state-o…
Score-Based Metropolis-Hastings Algorithms
Ahmed Aloui, Ali Hasan, Juncheng Dong +2
In this paper, we introduce a new approach for integrating score-based models with the Metropolis-Hastings algorithm. While traditional score-based diffusion models excel in accura…