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Qirong Ho

7 accepted papers

2026

Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters

ICLR 2026poster

On-device inference offers privacy, offline use, and instant response, but consumer hardware restricts large language models (LLMs) to low throughput and capability. To overcome this challenge, we present prima.cpp, a distributed on-device inference system that runs 30-70B LLMs on consumer home clus…

Cited by 0SourcecodeScholar
2025

A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection

EMNLP 2025

Rapid LLM advancements heighten fake news risks by enabling the automatic generation of increasingly sophisticated misinformation. Previous detection methods, including fine-tuned small models or LLM-based detectors, often struggle with its dynamically evolving nature. In this work, we propose a nov

Cited by 0SourcePDFScholar
2025

Linear Steerability in Language Models: When It Emerges and How It Evolves

EMNLP 2025

Language models can be steered by modifying their internal representations to control concepts such as emotion, style, or truthfulness in generation. However, the conditions for an effective intervention remain unclear and are often validated through heuristics and trial-and-error. To fill this gap,

Cited by 0SourcePDFScholar
2024

ActionIE: Action Extraction from Scientific Literature with Programming Languages

ACL 2024long

Extraction of experimental procedures from human language in scientific literature and patents into actionable sequences in robotics language holds immense significance in scientific domains. Such an action extraction task is particularly challenging given the intricate details and context-dependent…

2023

FedNAR: Federated Optimization with Normalized Annealing Regularization

NeurIPS 2023poster

Weight decay is a standard technique to improve generalization performance in modern deep neural network optimization, and is also widely adopted in federated learning (FL) to prevent overfitting in local clients. In this paper, we first explore the choices of weight decay and identify that weight d…

2023

Multi-level Adaptive Contrastive Learning for Knowledge Internalization in Dialogue Generation

EMNLP 2023long main

Knowledge-grounded dialogue generation aims to mitigate the issue of text degeneration by incorporating external knowledge to supplement the context. However, the model often fails to internalize this information into responses in a human-like manner. Instead, it simply inserts segments of the provi…

Cited by 0SourceScholar
2022

Unsupervised Image-to-Image Translation with Density Changing Regularization

NeurIPS 2022accept

Unpaired image-to-image translation aims to translate an input image to another domain such that the output image looks like an image from another domain while important semantic information are preserved. Inferring the optimal mapping with unpaired data is impossible without making any assumptions.…