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20242026
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cs.CL2026

PACER: Blockwise Pre-verification for Speculative Decoding with Adaptive Length

Situo Zhang, Yifan Zhang, Zichen Zhu +5

Speculative decoding (SD) is a powerful technique for accelerating the inference process of large language models (LLMs) without sacrificing accuracy. Typically, SD employs a small…

cs.CL2025

Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity

Da Ma, Lu Chen, Situo Zhang +8

The rapid expansion of context window sizes in Large Language Models~(LLMs) has enabled them to tackle increasingly complex tasks involving lengthy documents. However, this progres…

cs.CL2025

Developing ChemDFM as a large language foundation model for chemistry

Zihan Zhao, Da Ma, Lu Chen +11

Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…

cs.CL2025

Reducing Tool Hallucination via Reliability Alignment

Hongshen Xu, Zichen Zhu, Lei Pan +6

Large Language Models (LLMs) have expanded their capabilities beyond language generation to interact with external tools, enabling automation and real-world applications. However,…

cs.CL2024

SciDFM: A Large Language Model with Mixture-of-Experts for Science

Liangtai Sun, Danyu Luo, Da Ma +7

Recently, there has been a significant upsurge of interest in leveraging large language models (LLMs) to assist scientific discovery. However, most LLMs only focus on general scien…

cs.CL2024

SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research

Liangtai Sun, Yang Han, Zihan Zhao +5

Recently, there has been growing interest in using Large Language Models (LLMs) for scientific research. Numerous benchmarks have been proposed to evaluate the ability of LLMs for…