9 papers
LASAR: Latent Adaptive Semantic Aligned Reasoning for Generative Recommendation
Yiwen Chen, Fuwei Zhang, Zehao Chen +8
Large Language Models (LLMs) have demonstrated powerful reasoning capabilities through Chain-of-Thought (CoT) in various tasks, yet the inefficiency of token-by-token generation hi…
From 0-Order Selection to 2-Order Judgment: Combinatorial Hardening Exposes Compositional Failures in Frontier LLMs
Hanmeng Liu, Shichao Weng, Xiulai Liu +3
Multiple-choice reasoning benchmarks face dual challenges: rapid saturation from advancing models and data contamination that undermines static evaluations. Ad-hoc hardening method…
GeoSketch: A Neural-Symbolic Approach to Geometric Multimodal Reasoning with Auxiliary Line Construction and Affine Transformation
Shichao Weng, Zhiqiang Wang, Yuhua Zhou +5
Geometric Problem Solving (GPS) poses a unique challenge for Multimodal Large Language Models (MLLMs), requiring not only the joint interpretation of text and diagrams but also ite…
ReEfBench: Quantifying the Reasoning Efficiency of LLMs
Zhizhang Fu, Yuancheng Gu, Chenkai Hu +2
Test-time scaling has enabled Large Language Models (LLMs) to tackle complex reasoning, yet the limitations of current Chain-of-Thought (CoT) evaluation obscures whether performanc…
Multimodal Fusion And Sparse Attention-based Alignment Model for Long Sequential Recommendation
Yongrui Fu, Jian Liu, Tao Li +3
Recent advances in multimodal recommendation enable richer item understanding, while modeling users' multi-scale interests across temporal horizons has attracted growing attention.…
Evaluating the Logical Reasoning Abilities of Large Reasoning Models
Hanmeng Liu, Yiran Ding, Zhizhang Fu +3
Large reasoning models, often post-trained on long chain-of-thought (long CoT) data with reinforcement learning, achieve state-of-the-art performance on mathematical, coding, and d…