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Hengxing Cai

7 accepted papers

2026

Interpretable Reward Model via Sparse Autoencoder

AAAI 2026technical

Large language models (LLMs) have been widely deployed across numerous fields. Reinforcement Learning from Human Feedback (RLHF) leverages reward models (RMs) as proxies for human preferences to align LLM behaviors with human values, making the accuracy, reliability, and interpretability of RMs crit

Cited by 0SourcePDFScholar
2026

Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents

ICLR 2026poster

Large language models face challenges in long-context question answering, where key evidence of a query may be dispersed across millions of tokens. Existing works equip large language models with a memory corpus that is dynamically updated during a single-pass document scan, also known as the "memor…

Cited by 0SourcecodeScholar
2025

FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models

EMNLP 2025

Unmanned Aerial Vehicle (UAV) Vision-and-Language Navigation (VLN) is vital for applications such as disaster response, logistics delivery, and urban inspection. However, existing methods often struggle with insufficient multimodal fusion, weak generalization, and poor interpretability. To address t

2025

SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis

NAACL 2025findings

Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of LLMs in this domain, particularly in scenarios requiring higher-level abilities beyond mere memorization and the handli…

2025

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

ICLR 2025poster

Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarkable success of Large Language Models (LLMs), they face challenges in scientific literature understanding, primarily due…

2025

Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning

NeurIPS 2025poster

Large language models have demonstrated impressive reasoning capabilities but are inherently limited by their knowledge reservoir. Retrieval-augmented reasoning mitigates this limitation by allowing LLMs to query external resources, but existing methods often retrieve irrelevant or noisy information…

Cited by 0SourceScholar
2025

Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling

NeurIPS 2025poster

3D molecule generation is crucial for drug discovery and material science, requiring models to process complex multi-modalities, including atom types, chemical bonds, and 3D coordinates. A key challenge is integrating these modalities of different shapes while maintaining SE(3) equivariance for 3D c…

Cited by 0SourcecodeScholar