From the 1 of 6 linked papers with an AI index.
6 papers
Memory for Large Language Models
Sining Zhoubian, Dan Zhang, Evgeny Kharlamov +1
The paper surveys and categorizes the various memory mechanisms used in large language models, proposing a taxonomy based on representation, update dynamics, and persistence to uni…
Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding
Xuanming Zhang, Sining Zhoubian, Yuxuan Chen +8
Autoregressive generation in large language models (LLMs) conventionally decodes from the final layer, assuming that deeper representations yield more reliable next-token predictio…
ReST-RL: Achieving Accurate Code Reasoning of LLMs with Optimized Self-Training and Decoding
Sining Zhoubian, Dan Zhang, Jie Tang
With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method GRPO faces failure due to insignificant reward variance, while verif…
DataSciBench: An LLM Agent Benchmark for Data Science
Dan Zhang, Sining Zhoubian, Min Cai +7
This paper presents DataSciBench, a comprehensive benchmark for evaluating Large Language Model (LLM) capabilities in data science. Recent related benchmarks have primarily focused…
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search
Dan Zhang, Sining Zhoubian, Ziniu Hu +3
Recent methodologies in LLM self-training mostly rely on LLM generating responses and filtering those with correct output answers as training data. This approach often yields a low…
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models
Dan Zhang, Ziniu Hu, Sining Zhoubian +6
Large Language Models (LLMs) have shown promise in assisting scientific discovery. However, such applications are currently limited by LLMs' deficiencies in understanding intricate…