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20242026
most citedLlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

14 citations · 26 across the 25 of their papers we have counts for

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8 papers · 1 filter

cs.IR2026

DEPT: Document Embedding Preservation Tuning for Unified Query Expansion and Retrieval

Jingyuan Wang, Richong Zhang, Zhijie Nie +2

Large language models (LLMs) can both expand underspecified queries and encode text as dense representations, suggesting a unified model for query expansion and retrieval. Existing…

cs.SE2026

ExeCRE: Execution-Consistency Guided Reliability Estimation for Self-Correcting Code Generation

Yiru Dong, Richong Zhang, Fanshuang Kong +1

Large language models (LLMs) have made notable progress in code generation, but they still struggle on challenging tasks that require sophisticated algorithms or complex implementa…

cs.CV2026

Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models

Maham Nazir, Muhammad Aqeel, Richong Zhang +1

Multimodal video summarization requires visual features that align semantically with language generation. Traditional approaches rely on CNN features trained for object classificat…

stat.ML2026

Beyond Bellman: High-Order Generator Regression for Continuous-Time Policy Evaluation

Yaowei Zheng, Richong Zhang, Shenxi Wu +5

We study finite-horizon continuous-time policy evaluation from discrete closed-loop trajectories under time-inhomogeneous dynamics. The target value surface solves a backward parab…

cs.CL2026

CoRect: Context-Aware Logit Contrast for Hidden State Rectification to Resolve Knowledge Conflicts

Xuhua Ma, Richong Zhang, Zhijie Nie

Retrieval-Augmented Generation (RAG) often struggles with knowledge conflicts, where model-internal parametric knowledge overrides retrieved evidence, leading to unfaithful outputs…

cs.IR2026

Learning to Select: Query-Aware Adaptive Dimension Selection for Dense Retrieval

Zhanyu Wu, Richong Zhang, Zhijie Nie

Dense retrieval represents queries and documents as high-dimensional embeddings, but these representations can be redundant at the query level: for a given information need, only a…

cs.CL2026

AR-BENCH: Benchmarking Legal Reasoning with Judgment Error Detection, Classification and Correction

Yifei Li, Richong Zhang, Wanyu Tu +4

Legal judgments may contain errors due to the complexity of case circumstances and the abstract nature of legal concepts, while existing appellate review mechanisms face efficiency…

cs.CL2026

inversedMixup: Data Augmentation via Inverting Mixed Embeddings

Fanshuang Kong, Richong Zhang, Qiyu Sun +3

Mixup generates augmented samples by linearly interpolating inputs and labels with a controllable ratio. However, since it operates at the latent embedding level, the resulting sam…