2 citations · 8 across the 12 of their papers we have counts for
12 papers
Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark
Ziming Cheng, Binrui Xu, Lisheng Gong +14
With enhanced capabilities and widespread applications, Multimodal Large Language Models (MLLMs) are increasingly required to process and reason over multiple images simultaneously…
Boosting LLM via Learning from Data Iteratively and Selectively
Qi Jia, Siyu Ren, Ziheng Qin +3
Datasets nowadays are generally constructed from multiple sources and using different synthetic techniques, making data de-noising and de-duplication crucial before being used for…
On the Efficacy of Eviction Policy for Key-Value Constrained Generative Language Model Inference
Siyu Ren, Kenny Q. Zhu
Despite the recent success associated with Large Language Models (LLMs), they are notably cost-prohibitive to deploy in resource-constrained environments due to their excessive mem…
Context Compression for Auto-regressive Transformers with Sentinel Tokens
Siyu Ren, Qi Jia, Kenny Q. Zhu
The quadratic complexity of the attention module makes it gradually become the bulk of compute in Transformer-based LLMs during generation. Moreover, the excessive key-value cache…
Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model
Qi Jia, Siyu Ren, Yizhu Liu +1
Despite tremendous improvements in natural language generation, summarization models still suffer from the unfaithfulness issue. Previous work evaluates faithfulness either using m…
EMO: Earth Mover Distance Optimization for Auto-Regressive Language Modeling
Siyu Ren, Zhiyong Wu, Kenny Q. Zhu
Neural language models are probabilistic models of human text. They are predominantly trained using maximum likelihood estimation (MLE), which is equivalent to minimizing the forwa…
Low-Rank Prune-And-Factorize for Language Model Compression
Siyu Ren, Kenny Q. Zhu
The components underpinning PLMs -- large weight matrices -- were shown to bear considerable redundancy. Matrix factorization, a well-established technique from matrix theory, has…
Pruning Pre-trained Language Models with Principled Importance and Self-regularization
Siyu Ren, Kenny Q. Zhu
Iterative pruning is one of the most effective compression methods for pre-trained language models. We discovered that finding the optimal pruning decision is an equality-constrain…
Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions
Qi Jia, Yizhu Liu, Siyu Ren +1
Abstractive dialogue summarization is to generate a concise and fluent summary covering the salient information in a dialogue among two or more interlocutors. It has attracted grea…
Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval
Siyu Ren, Kenny Q. Zhu
Current text-image approaches (e.g., CLIP) typically adopt dual-encoder architecture using pre-trained vision-language representation. However, these models still pose non-trivial…
Multi-turn Response Selection using Dialogue Dependency Relations
Qi Jia, Yizhu Liu, Siyu Ren +2
Multi-turn response selection is a task designed for developing dialogue agents. The performance on this task has a remarkable improvement with pre-trained language models. However…
Knowledge-Driven Distractor Generation for Cloze-style Multiple Choice Questions
Siyu Ren, Kenny Q. Zhu
In this paper, we propose a novel configurable framework to automatically generate distractive choices for open-domain cloze-style multiple-choice questions, which incorporates a g…