5 citations · 15 across the 19 of their papers we have counts for
10 papers · 1 filter
CTkvr: KV Cache Retrieval for Long-Context LLMs via Centroid then Token Indexing
Kuan Lu, Shuhang Lin, Sai Wu +7
Large language models (LLMs) are increasingly applied in long-context scenarios such as multi-turn conversations. However, long contexts pose significant challenges for inference e…
MOTION: ML-Assisted On-Device Low-Latency Motion Recognition
Veeramani Pugazhenthi, Wei-Hsiang Chu, Junwei Lu +5
The use of tiny devices capable of low-latency gesture recognition is gaining momentum in everyday human-computer interaction and especially in medical monitoring fields. Embedded…
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing
Baode Wang, Biao Wu, Weizhen Li +8
Document parsing from scanned images into structured formats remains a significant challenge due to its complexly intertwined elements such as text paragraphs, figures, formulas, a…
OleSpeech-IV: A Large-Scale Multispeaker and Multilingual Conversational Speech Dataset with Diverse Topics
Wei Chu, Yuanzhe Dong, Ke Tan +7
OleSpeech-IV dataset is a large-scale multispeaker and multilingual conversational speech dataset with diverse topics. The audio content comes from publicly-available English podca…
The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward
Long Li, Zhijian Zhou, Jiaran Hao +9
A central paradox in fine-tuning Large Language Models (LLMs) with Reinforcement Learning with Verifiable Reward (RLVR) is the frequent degradation of multi-attempt performance (Pa…
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing
Baode Wang, Biao Wu, Weizhen Li +8
Automated parsing of scanned documents into richly structured, machine-readable formats remains a critical bottleneck in Document AI, as traditional multi-stage pipelines suffer fr…
Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning
Shuyao Xu, Cheng Peng, Jiangxuan Long +3
Recent advances in model distillation show that data from advanced reasoning models can effectively train smaller student models. However, standard practices discard incorrect reas…
Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents
Rui Xu, MingYu Wang, XinTao Wang +4
Recent advances in LLM-based role-playing language agents (RPLAs) have attracted broad attention in various applications. While chain-of-thought reasoning has shown importance in m…
To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization
Haozhe Wang, Long Li, Chao Qu +4
Recent advances in mathematical problem-solving with language models (LMs) integrate chain-of-thought (CoT) reasoning and code execution to harness their complementary strengths. H…
SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain
Dakuan Lu, Xiaoyu Tan, Rui Xu +5
Recent breakthroughs in large language models (LLMs) exemplified by the impressive mathematical and scientific reasoning capabilities of the o1 model have spotlighted the critical…