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Wenxuan Shi

7 accepted papers

2026

Safety Alignment of Large Language Models via Contrasting Safe and Harmful Distributions

AAAI 2026technical

With the widespread application of Large Language Models (LLMs), it has become a significant concern to ensure their safety and prevent harmful responses. While current safe-alignment methods based on instruction fine-tuning and Reinforcement Learning from Human Feedback (RLHF) can effectively reduc

Cited by 0SourcePDFScholar
2025

DeepDiver: Adaptive Web-Search Intensity Scaling via Reinforcement Learning

NeurIPS 2025spotlight

Information seeking demands iterative evidence gathering and reflective reasoning, yet large language models (LLMs) still struggle with it in open-web question answering. Existing prompting and supervised fine-tuning (SFT) methods remain fixed by prompt rules or training corpora, and are usually ben…

Cited by 0SourceScholar
2025

Hierarchical Memory Organization for Wikipedia Generation

ACL 2025long

Generating Wikipedia articles autonomously is a challenging task requiring the integration of accurate, comprehensive, and well-structured information from diverse sources. This paper introduces the Memory Organization-based Generation (MOG) framework, a novel approach to address these challenges by…

2025

InverseCoder: Self-improving Instruction-Tuned Code LLMs with Inverse-Instruct

AAAI 2025technical

Recent advancements in open-source code large language models (LLMs) have been driven by fine-tuning on the data generated from powerful closed-source LLMs, which are expensive to obtain. This paper explores whether it is possible to use a fine-tuned open-source model to generate additional data to…

2025

QiMeng-CodeV-R1: Reasoning-Enhanced Verilog Generation

NeurIPS 2025poster

Large language models (LLMs) trained via reinforcement learning with verifiable reward (RLVR) have achieved breakthroughs on tasks with explicit, automatable verification, such as software programming and mathematical problems. Extending RLVR to electronic design automation (EDA), especially automat…

Cited by 0SourceScholar
2022

Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis

ACL 2022long

The state-of-the-art model for structured sentiment analysis casts the task as a dependency parsing problem, which has some limitations: (1) The label proportions for span prediction and span relation prediction are imbalanced. (2) The span lengths of sentiment tuple components may be very large in…

2022

Entity-centered Cross-document Relation Extraction

EMNLP 2022main

Relation Extraction (RE) is a fundamental task of information extraction, which has attracted a large amount of research attention. Previous studies focus on extracting the relations within a sentence or document, while currently researchers begin to explore cross-document RE. However, current cross…