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Zhiting Hu

Papers
23

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23papers

Authored papers

23

CocoaBench: Evaluating Unified Digital Agents in the Wild

arXiv 2026

2026

FIRE-Bench: Evaluating Agents on the Rediscovery of Scientific Insights

arXiv 2026

2026

scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery

arXiv 2026

2026

CellMaster: Collaborative Cell Type Annotation in Single-Cell Analysis

arXiv 2026

2026

SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds

arXiv 2025

2025

Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective

arXiv 2025

2025

Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play

arXiv 2025

2025

Training Large Language Models to Reason in a Continuous Latent Space

arXiv 2024

2024

MMToM-QA: Multimodal Theory of Mind Question Answering

arXiv 2024

2024

Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models

arXiv 2024

2024

Pandora: Towards General World Model with Natural Language Actions and Video States

arXiv 2024

2024

ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

toolkengpt-augmenting-frozen-language-models

2023

AlignScore: Evaluating Factual Consistency with a Unified Alignment Function

arXiv 2023

2023

Language Models Meet World Models: Embodied Experiences Enhance Language Models

language-models-meet-world-models-embodied

2023

LLM360: Towards Fully Transparent Open-Source LLMs

arXiv 2023

2023

RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs

arXiv 2023

2023

RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

arXiv 2022

2022

BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models

arXiv 2022

2022

Composable Text Controls in Latent Space with ODEs

arXiv 2022

2022

Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation

EMNLP 2021 11

2021

Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation

don-t-take-it-literally-an-edit-invariant-1

2021

A Survey of Knowledge-Enhanced Text Generation

arXiv 2020

2020

Text Infilling

arXiv 2019

2019

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from 23 papers