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cs.CL2026

Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models

Bin Cao, Huixian Lu, Chenwen Ma +3

Complex tables with multi-level headers, merged cells and heterogeneous layouts pose persistent challenges for LLMs in both understanding and reasoning. Existing approaches typical…

cs.CL2026

On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation

Weichuan Wang, Mingyang Liu, Linqi Song +1

In recent years, the non-deterministic properties of language models have garnered considerable attention and have shown a significant influence on real-world applications. However…

cs.CL2025

NILE: Internal Consistency Alignment in Large Language Models

Minda Hu, Qiyuan Zhang, Yufei Wang +7

As a crucial step to enhance LLMs alignment with human intentions, Instruction Fine-Tuning (IFT) has a high demand on dataset quality. However, existing IFT datasets often contain…

cs.CL2025

A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Qiyuan Zhang, Fuyuan Lyu, Zexu Sun +10

As enthusiasm for scaling computation (data and parameters) in the pretraining era gradually diminished, test-time scaling (TTS), also referred to as ``test-time computing'' has em…

cs.CL2025

Crowd Comparative Reasoning: Unlocking Comprehensive Evaluations for LLM-as-a-Judge

Qiyuan Zhang, Yufei Wang, Yuxin Jiang +8

LLM-as-a-Judge, which generates chain-of-thought (CoT) judgments, has become a widely adopted auto-evaluation method. However, its reliability is compromised by the CoT reasoning's…

cs.CL2025

RevisEval: Improving LLM-as-a-Judge via Response-Adapted References

Qiyuan Zhang, Yufei Wang, Tiezheng YU +9

With significant efforts in recent studies, LLM-as-a-Judge has become a cost-effective alternative to human evaluation for assessing text generation quality in a wide range of task…