13 citations · 15 across the 9 of their papers we have counts for
9 papers
A Formal Kinetic Theory for Zeroth-Order Newton Dynamics:Stein-Corrected Hessian Estimation and Curvature--Variance Trade-offs
Shihao Ji, Mingyu Li, Zihui Song
Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-free methods. We develop a kine…
OraclePhys: A Systematic Framework for LLM Fine-Tuning on Structural Mechanics
Mingyu Li, Guorui Song, Jing Lin +1
What a language model internalizes from fine-tuning is usually diagnosed after the fact. We make it an experimental variable. OraclePhys is a systematic fine-tuning framework with…
Lagrange: An Open-Vocabulary, Energy-Based Sparse Framework for Generalized End-to-End Driving
Shihao Ji, HongXi Li, Zihui Song +1
Scaling end-to-end autonomous driving to complex, open-world environments requires perceptual models that generalize to anomalous scenarios and planners that produce kinematically…
Expected Value Alignment for Generative Reward Modeling in Formal Mathematics Verification
Shihao Ji, Haotao Tan, Zihui Song +1
Large Language Models (LLMs) are increasingly used with formal interactive theorem provers such as Lean 4. Scaling these systems with reinforcement learning or search methods requi…
Soft-NBCE: Entropy-Weighted Chunk Fusion for Long-Context
Shihao Ji, Mingyu Li, Zihui Song
The quadratic complexity of self-attention remains a bottleneck for Large Language Models (LLMs) processing ultra-long contexts. The Naive Bayes Cognitive Engine (NBCE) parallelize…
E-comIQ-ZH: A Human-Aligned Dataset and Benchmark for Fine-Grained Evaluation of E-commerce Posters with Chain-of-Thought
Meiqi Sun, Mingyu Li, Junxiong Zhu
Generative AI is widely used to create commercial posters. However, rapid advances in generation have outpaced automated quality assessment. Existing models emphasize generic esthe…
A Survey of Context Engineering for Large Language Models
Lingrui Mei, Jiayu Yao, Yuyao Ge +12
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a f…
1Cademy @ Causal News Corpus 2022: Leveraging Self-Training in Causality Classification of Socio-Political Event Data
Adam Nik, Ge Zhang, Xingran Chen +2
This paper details our participation in the Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) workshop @ EMNLP 2022, where we take part…
1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position Selector
Xingran Chen, Ge Zhang, Adam Nik +2
In this paper, we present our approach and empirical observations for Cause-Effect Signal Span Detection -- Subtask 2 of Shared task 3~\cite{tan-etal-2022-event} at CASE 2022. The…