2 citations · 2 across the 6 of their papers we have counts for
6 papers
DeepLook: Uncertainty-Guided Branching with Lookahead Confidence for Efficient Reasoning
Tingxin Yang, Zefeng Wang, Mengyue Wang +4
Test-time scaling improves large language model reasoning, but spends compute uniformly along a reasoning trace, even in stretches that are already stable. Motivated by the observa…
Customized User Plane Processing via Code Generating AI Agents for Next Generation Mobile Networks
Xiaowen Ma, Onur Ayan, Yunpu Ma +1
Generative AI is envisioned to have a crucial impact on next generation mobile networking, making the sixth generation (6G) system considerably more autonomous, flexible, and adapt…
Policy of Thoughts: Scaling Test-Time Training for LLM Reasoning via Online Policy Evolution
Zhengbo Jiao, Hongyu Xian, Qinglong Wang +5
Large language models (LLMs) struggle with complex, long-horizon reasoning due to instability caused by their frozen policy assumption. Current test-time scaling methods treat exec…
Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
Sikuan Yan, Xiufeng Yang, Zuchao Huang +10
Large Language Models (LLMs) have demonstrated impressive capabilities across a wide range of NLP tasks, but they remain fundamentally stateless, constrained by limited context win…
ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge
Zeinab Sadat Taghavi, Ali Modarressi, Yunpu Ma +1
Retrieval systems are central to many NLP pipelines, but often rely on surface-level cues such as keyword overlap and lexical semantic similarity. To evaluate retrieval beyond thes…
Language Mixing in Reasoning Language Models: Patterns, Impact, and Internal Causes
Mingyang Wang, Lukas Lange, Heike Adel +3
Reasoning language models (RLMs) excel at complex tasks by leveraging a chain-of-thought process to generate structured intermediate steps. However, language mixing, i.e., reasonin…