1 code implementation • 4 Apr 2025 • Runnan Fang, Xiaobin Wang, Yuan Liang, Shuofei Qiao, Jialong Wu, Zekun Xi, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen
In the interaction between agents and their environments, agents expand their capabilities by planning and executing actions.
no code implementations • 13 Mar 2025 • Jialong Wu, Marco Braun, Dominic Spata, Matthias Rottmann
Scene flow provides crucial motion information for autonomous driving.
1 code implementation • 12 Mar 2025 • Zhaoling Chen, Xiangru Tang, Gangda Deng, Fang Wu, Jialong Wu, Zhiwei Jiang, Viktor Prasanna, Arman Cohan, Xingyao Wang
By parsing codebases into directed heterogeneous graphs, LocAgent creates a lightweight representation that captures code structures (files, classes, functions) and their dependencies (imports, invocations, inheritance), enabling LLM agents to effectively search and locate relevant entities through powerful multi-hop reasoning.
no code implementations • 3 Mar 2025 • Linhai Zhang, Jialong Wu, Deyu Zhou, Yulan He
Personalized large language models (LLMs) aim to tailor their outputs to user preferences.
1 code implementation • 24 Feb 2025 • Zhenglin Wang, Jialong Wu, Pengfei Li, Yong Jiang, Deyu Zhou
Temporal reasoning is fundamental to human cognition and is crucial for various real-world applications.
1 code implementation • 16 Jan 2025 • Zekun Xi, Wenbiao Yin, Jizhan Fang, Jialong Wu, Runnan Fang, Ningyu Zhang, Jiang Yong, Pengjun Xie, Fei Huang, Huajun Chen
Machine writing with large language models often relies on retrieval-augmented generation.
1 code implementation • 13 Jan 2025 • Jialong Wu, Wenbiao Yin, Yong Jiang, Zhenglin Wang, Zekun Xi, Runnan Fang, Linhai Zhang, Yulan He, Deyu Zhou, Pengjun Xie, Fei Huang
Extensive experimental results show that WebWalkerQA is challenging and demonstrates the effectiveness of RAG combined with WebWalker, through the horizontal and vertical integration in real-world scenarios.
no code implementations • 18 Dec 2024 • Jialong Wu, Zhenglin Wang, Linhai Zhang, Yilong Lai, Yulan He, Deyu Zhou
Key-Value (KV) cache has become a bottleneck of LLMs for long-context generation.
1 code implementation • 17 Oct 2024 • Siwei Wu, Zhongyuan Peng, Xinrun Du, Tuney Zheng, Minghao Liu, Jialong Wu, Jiachen Ma, Yizhi Li, Jian Yang, Wangchunshu Zhou, Qunshu Lin, Junbo Zhao, Zhaoxiang Zhang, Wenhao Huang, Ge Zhang, Chenghua Lin, J. H. Liu
In our work, to investigate the reasoning patterns of o1, we compare o1 with existing Test-time Compute methods (BoN, Step-wise BoN, Agent Workflow, and Self-Refine) by using OpenAI's GPT-4o as a backbone on general reasoning benchmarks in three domains (i. e., math, coding, commonsense reasoning).
1 code implementation • 3 Oct 2024 • Ningya Feng, Junwei Pan, Jialong Wu, Baixu Chen, Ximei Wang, Qian Li, Xian Hu, Jie Jiang, Mingsheng Long
In this work, we identify and characterize, for the first time, a neglected deficiency in existing long-sequence recommendation models: a single set of embeddings struggles with learning both attention and representation, leading to interference between these two processes.
1 code implementation • 2 Jul 2024 • Yilong Lai, Jialong Wu, Congzhi Zhang, Haowen Sun, Deyu Zhou
Conversational Query Reformulation (CQR) has significantly advanced in addressing the challenges of conversational search, particularly those stemming from the latent user intent and the need for historical context.
1 code implementation • 26 Jun 2024 • Wangchunshu Zhou, Yixin Ou, Shengwei Ding, Long Li, Jialong Wu, Tiannan Wang, Jiamin Chen, Shuai Wang, Xiaohua Xu, Ningyu Zhang, Huajun Chen, Yuchen Eleanor Jiang
In this work, we introduce agent symbolic learning, a systematic framework that enables language agents to optimize themselves on their own in a data-centric way using symbolic optimizers.
1 code implementation • 26 Jun 2024 • Zhenglin Wang, Jialong Wu, Yilong Lai, Congzhi Zhang, Deyu Zhou
However, such methods introduce significant inference latency due to the systematic exploration and evaluation of multiple thought paths.
no code implementations • 15 Jun 2024 • Jialong Wu, Mirko Meuter, Markus Schoeler, Matthias Rottmann
Radar-based perception has gained increasing attention in autonomous driving, yet the inherent sparsity of radars poses challenges.
1 code implementation • 24 May 2024 • Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, Mingsheng Long
This work introduces Interactive VideoGPT (iVideoGPT), a scalable autoregressive transformer framework that integrates multimodal signals--visual observations, actions, and rewards--into a sequence of tokens, facilitating an interactive experience of agents via next-token prediction.
no code implementations • 24 Apr 2024 • Chaoyi Deng, Jialong Wu, Ningya Feng, Jianmin Wang, Mingsheng Long
Effective code optimization in compilers is crucial for computer and software engineering.
no code implementations • 5 Mar 2024 • Congzhi Zhang, Linhai Zhang, Jialong Wu, Yulan He, Deyu Zhou
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges related to various biases.
1 code implementation • 2 Mar 2024 • Linhai Zhang, Jialong Wu, Deyu Zhou, Guoqiang Xu
For poor model calibration, we incorporate the regularization method during LoRA training to keep the model from being over-confident, and the Monte-Carlo dropout mechanism is employed to enhance the uncertainty estimation.
1 code implementation • 2 Mar 2024 • Jialong Wu, Linhai Zhang, Deyu Zhou, Guoqiang Xu
However, most of the present debiasing methods focus on single-variable causal inference, which is not suitable for ABSA with two input variables (the target aspect and the review).
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
no code implementations • 30 Jan 2024 • Tiannan Wang, Jiamin Chen, Qingrui Jia, Shuai Wang, Ruoyu Fang, Huilin Wang, Zhaowei Gao, Chunzhao Xie, Chuou Xu, Jihong Dai, Yibin Liu, Jialong Wu, Shengwei Ding, Long Li, Zhiwei Huang, Xinle Deng, Teng Yu, Gangan Ma, Han Xiao, Zixin Chen, Danjun Xiang, Yunxia Wang, Yuanyuan Zhu, Yi Xiao, Jing Wang, Yiru Wang, Siran Ding, Jiayang Huang, Jiayi Xu, Yilihamu Tayier, Zhenyu Hu, Yuan Gao, Chengfeng Zheng, Yueshu Ye, Yihang Li, Lei Wan, Xinyue Jiang, Yujie Wang, Siyu Cheng, Zhule Song, Xiangru Tang, Xiaohua Xu, Ningyu Zhang, Huajun Chen, Yuchen Eleanor Jiang, Wangchunshu Zhou
Weaver is pre-trained on a carefully selected corpus that focuses on improving the writing capabilities of large language models.
no code implementations • 30 Oct 2023 • Xuefeng Bai, Jialong Wu, Yulong Chen, Zhongqing Wang, Yue Zhang
Constituency parsing is a fundamental yet unsolved natural language processing task.
1 code implementation • 30 Sep 2023 • Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long
Model-based reinforcement learning (MBRL) holds the promise of sample-efficient learning by utilizing a world model, which models how the environment works and typically encompasses components for two tasks: observation modeling and reward modeling.
Ranked #4 on
Atari Games 100k
on Atari 100k
1 code implementation • 14 Sep 2023 • Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shi Qiu, Jintian Zhang, Jing Chen, Ruipu Wu, Shuai Wang, Shiding Zhu, Jiyu Chen, Wentao Zhang, Xiangru Tang, Ningyu Zhang, Huajun Chen, Peng Cui, Mrinmaya Sachan
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
1 code implementation • NeurIPS 2023 • Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long
To tackle this issue, we introduce Contextualized World Models (ContextWM) that explicitly separate context and dynamics modeling to overcome the complexity and diversity of in-the-wild videos and facilitate knowledge transfer between distinct scenes.
1 code implementation • 2 Feb 2023 • Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long
This paper aims at generalizing CLIP to out-of-distribution test data on downstream tasks.
1 code implementation • 13 Nov 2022 • Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long
Existing imitation learning works mainly assume that the demonstrator who collects demonstrations shares the same dynamics as the imitator.
no code implementations • 11 Jul 2022 • Walter Zimmer, Jialong Wu, Xingcheng Zhou, Alois C. Knoll
This work aims to address the challenges in autonomous driving by focusing on the 3D perception of the environment using roadside LiDARs.
1 code implementation • 13 Feb 2022 • Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long
By respectively conserving the incoming flow of sinks for source competition and the outgoing flow of sources for sink allocation, Flow-Attention inherently generates informative attentions without using specific inductive biases.
Ranked #4 on
D4RL
on D4RL
3 code implementations • 13 Feb 2022 • Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long
Policy constraint methods to offline reinforcement learning (RL) typically utilize parameterization or regularization that constrains the policy to perform actions within the support set of the behavior policy.