1 citations · 1 across the 13 of their papers we have counts for
13 papers
ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation
Weichu Liu, Yuxuan Hu, Yirong Sun +6
Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. However, existing methods strugg…
Think-as-You-See: Streaming Chain-of-Thought Reasoning for Large Vision-Language Models
Jialiang Zhang, Junlong Tong, Junyan Lin +4
Large Vision Language Models (LVLMs) exhibit strong Chain-of-Thought (CoT) capabilities, yet most existing paradigms assume full-video availability before inference, a batch-style…
Rethinking the Role of LLMs in Time Series Forecasting
Xin Qiu, Junlong Tong, Yirong Sun +3
Large language models (LLMs) have been introduced to time series forecasting (TSF) to incorporate contextual knowledge beyond numerical signals. However, existing studies question…
The Trace Is the State: Exact Credit Assignment for LLM Agent Teams
Yanjun Chen, Yirong Sun, Hanlin Wang +5
Credit assignment for a team of LLM agents, what each message was worth, has mostly been treated as prediction: a learned critic, a trajectory-level score, or an agent ablation sta…
SonicBench: Dissecting the Physical Perception Bottleneck in Large Audio Language Models
Yirong Sun, Yanjun Chen, Xin Qiu +8
Large Audio Language Models (LALMs) excel at semantic and paralinguistic tasks, yet their ability to perceive the fundamental physical attributes of audio such as pitch, loudness,…
The Few Govern the Many:Unveiling Few-Layer Dominance for Time Series Models
Xin Qiu, Junlong Tong, Yirong Sun +2
Large-scale models are at the forefront of time series (TS) forecasting, dominated by two paradigms: fine-tuning text-based Large Language Models (LLM4TS) and training Time Series…
LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model
Yirong Sun, Yizhong Geng, Peidong Wei +5
The development of Large Speech-Language Models (LSLMs) has been slowed by fragmented architectures and a lack of transparency, hindering the systematic comparison and reproducibil…
PRISM: Preference Refinement via Implicit Scene Modeling for 3D Vision-Language Preference-Based Reinforcement Learning
Yirong Sun, Yanjun Chen
We propose PRISM, a novel framework designed to overcome the limitations of 2D-based Preference-Based Reinforcement Learning (PBRL) by unifying 3D point cloud modeling and future-a…
Integrating Chain-of-Thought for Multimodal Alignment: A Study on 3D Vision-Language Learning
Yanjun Chen, Yirong Sun, Xinghao Chen +4
Chain-of-Thought (CoT) reasoning has proven effective in natural language tasks but remains underexplored in multimodal alignment. This study investigates its integration into 3D v…
Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning
Xinghao Chen, Zhijing Sun, Wenjin Guo +8
Large Language Models (LLMs) excel in reasoning tasks through Chain-of-Thought (CoT) prompting. However, CoT prompting greatly increases computational demands, which has prompted g…
Breaking the Pre-Planning Barrier: Adaptive Real-Time Coordination of Heterogeneous UAVs
Yuhan Hu, Yirong Sun, Yanjun Chen +3
Unmanned Aerial Vehicles (UAVs) offer significant potential in dynamic, perception-intensive tasks such as search and rescue and environmental monitoring; however, their effectiven…
The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models
Yanjun Chen, Dawei Zhu, Yirong Sun +3
Reinforcement Learning from Human Feedback significantly enhances Natural Language Processing by aligning language models with human expectations. A critical factor in this alignme…
Fine-Grained and Multi-Dimensional Metrics for Document-Level Machine Translation
Yirong Sun, Dawei Zhu, Yanjun Chen +3
Large language models (LLMs) have excelled in various NLP tasks, including machine translation (MT), yet most studies focus on sentence-level translation. This work investigates th…