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Zirui Zhao

7 accepted papers

2025

Automatic Curriculum Expert Iteration for Reliable LLM Reasoning

ICLR 2025poster

Hallucinations (i.e., generating plausible but inaccurate content) and laziness (i.e. excessive refusals or defaulting to "I don't know") persist as major challenges in LLM reasoning. Current efforts to reduce hallucinations primarily focus on factual errors in knowledge-grounded tasks, often neglec…

2025

Walk in Others’ Shoes with a Single Glance: Human-Centric Visual Grounding with Top-View Perspective Transformation

ACL 2025long

Visual perspective-taking, an ability to envision others’ perspectives from a single self-perspective, is vital in human-robot interactions. Thus, we introduce a human-centric visual grounding task and a dataset to evaluate this ability. Recent advances in vision-language models (VLMs) have shown po…

2024

On the Empirical Complexity of Reasoning and Planning in LLMs

EMNLP 2024finding

Chain-of-thought (CoT), tree-of-thought (ToT), and related techniques work surprisingly well in practice for some complex reasoning tasks with Large Language Models (LLMs), but why? This work seeks the underlying reasons by conducting experimental case studies and linking the performance benefits to…

2024

Seamless Virtual Reality With Integrated Synchronizer and Synthesizer for Autonomous Driving

RA-L 2024

Virtual reality (VR) is a promising data engine for autonomous driving (AD). However, data fidelity in this paradigm is often degraded by VR inconsistency, for which the existing VR approaches become ineffective, as they ignore the inter-dependency between low-level VR synchronizer designs (i.e., da

Cited by 8SourceScholar
2023

Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement

ICRA 2023poster

We present a new method, PARsing And visual GrOuNding (PARAGON), for grounding natural language in object placement tasks. Natural language generally describes objects and spatial relations with compositionality and ambiguity, two major obstacles to effective language grounding. For compositionality…

Cited by 11SourceScholar