update publications

Author: jiachenli94

_cite/.cache/cache.db

@@ -160,6 +160,33 @@
   - Explainability/Interpretability
   plugin: sources.py
   file: sources.yaml
+- title: 'RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon
+    Tasks'
+  authors:
+  - M. Yan
+  - Y. Wang
+  - Z. Liu
+  - and J. Li
+  publisher: ' 39th Conference on Neural Information Processing Systems (NeurIPS 2025)'
+  date: '2025-10-16'
+  image: ./paper_images/rdd.png
+  buttons:
+  - type: paper_link
+    text: arXiv
+    link: https://arxiv.org/abs/2510.14968
+  - type: paper_home
+    text: Website
+    link: http://rdd-neurips.github.io/
+  - type: paper_code
+    text: Code
+    link: https://github.com/tasl-lab/RDD
+  tags:
+  - Robot Learning
+  - Robot Manipulation
+  - Long-Horizon Tasks
+  - Vision-Language-Action Models
+  plugin: sources.py
+  file: sources.yaml
 - title: Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty
     Handling
   authors:
@@ -187,6 +214,7 @@
     link: https://github.com/tasl-lab/GenSafeNav
   tags:
   - Social Navigation
+  - Robot Learning
   - Human-Robot Interaction/Collaboration
   - Safety
   - Generalization/Robustness

_data/citations.yaml

@@ -171,10 +171,30 @@
 
 
 
-
-
-
-
+- title: "RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Tasks"
+  authors:
+    - M. Yan
+    - Y. Wang
+    - Z. Liu
+    - and J. Li
+  publisher: " 39th Conference on Neural Information Processing Systems (NeurIPS 2025)"
+  date: 2025-10-16
+  image: ./paper_images/rdd.png
+  buttons:
+    - type: paper_link
+      text: arXiv
+      link: https://arxiv.org/abs/2510.14968
+    - type: paper_home
+      text: Website
+      link: http://rdd-neurips.github.io/
+    - type: paper_code
+      text: Code
+      link: https://github.com/tasl-lab/RDD
+  tags:
+    - Robot Learning
+    - Robot Manipulation
+    - Long-Horizon Tasks
+    - Vision-Language-Action Models
 
 
 
@@ -205,6 +225,7 @@
       link: https://github.com/tasl-lab/GenSafeNav
   tags:
     - Social Navigation
+    - Robot Learning
     - Human-Robot Interaction/Collaboration
     - Safety
     - Generalization/Robustness

_data/sources.yaml

@@ -5,7 +5,7 @@ nav:
 ---
 
 # {% include icon.html icon="fa-solid fa-newspaper" %}News
-- 09/2025: [One paper](https://tasl.ucr.edu/news/) is accepted at Annual Conference on Neural Information Processing Systems (NeurIPS 2025)!
+- 09/2025: [One paper](http://arxiv.org/abs/2510.14968) is accepted at Annual Conference on Neural Information Processing Systems (NeurIPS 2025)!
 - 09/2025: Prof. Li is invited to serve on the Organizing Committee for RSS 2026!
 - 08/2025: Prof. Li received a research grant from NSF to investigate Trustworthy and Resilient Intelligence for Multi-Agent Systems!
 - 08/2025: Prof. Li will give an invited keynote talk at the [DriveX Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving](https://drivex-workshop.github.io/) at ICCV 2025!

news/index.md

@@ -8,7 +8,7 @@ nav:
 
 **Please refer to Prof. Jiachen Li's [Google Scholar](https://scholar.google.com/citations?user=1_f79vUAAAAJ&hl) for a complete list of publications.**
 
-{% include tags.html tags="Social Navigation, Autonomous Driving, Human-Robot Interaction/Collaboration, Embodied AI, Foundation Models, Vision-Language, Multi-Agent/Robot Systems, Mobile Manipulation, Cooperative Perception, Reinforcement Learning, Graph Neural Networks, Generative Models, Relational Reasoning, Safety, Generalization/Robustness, Uncertainty Quantification, Explainability/Interpretability, Meta Learning, Trajectory Prediction, Occupancy Prediction, Human Intention/Motion Prediction, Multi-Object Tracking, Survey" %}
+{% include tags.html tags="Social Navigation, Robot Manipulation, Autonomous Driving, Robot Learning, Human-Robot Interaction/Collaboration, Embodied AI, Foundation Models, Vision-Language, Vision-Language-Action Models, Multi-Agent/Robot Systems, Mobile Manipulation, Cooperative Perception, Reinforcement Learning, Graph Neural Networks, Generative Models, Relational Reasoning, Safety, Generalization/Robustness, Uncertainty Quantification, Explainability/Interpretability, Meta Learning, Trajectory Prediction, Occupancy Prediction, Human Intention/Motion Prediction, Multi-Object Tracking, Survey" %}
 
 {% include search-box.html %}
 
@@ -19,6 +19,7 @@ nav:
 ## Recent Highlights
 
 {% include citation.html lookup="Internal State Inference" style="rich" %}
+{% include citation.html lookup="RDD" style="rich" %}
 {% include citation.html lookup="Towards Generalizable Safety" style="rich" %}
 {% include citation.html lookup="UniOcc" style="rich" %}
 {% include citation.html lookup="LaMMA-P" style="rich" %}