activity
20232026
most citedAuto Search Indexer for End-to-End Document Retrieval

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning

Yunan Wang, Minghui Song, Zihan Zhang +6

Group-based Reinforcement Learning (RL) has significantly enhanced Large Language Models (LLMs) in agentic scenarios. To achieve finer-grained policy updates, recent agentic RL fra…

cs.CL2024★ 1 cited

E5-V: Universal Embeddings with Multimodal Large Language Models

Ting Jiang, Minghui Song, Zihan Zhang +6

Multimodal large language models (MLLMs) have shown promising advancements in general visual and language understanding. However, the representation of multimodal information using…

cs.IR2024

ASI++: Towards Distributionally Balanced End-to-End Generative Retrieval

Yuxuan Liu, Tianchi Yang, Zihan Zhang +5

Generative retrieval, a promising new paradigm in information retrieval, employs a seq2seq model to encode document features into parameters and decode relevant document identifier…

cs.CL2024

ResLoRA: Identity Residual Mapping in Low-Rank Adaption

Shuhua Shi, Shaohan Huang, Minghui Song +7

As one of the most popular parameter-efficient fine-tuning (PEFT) methods, low-rank adaptation (LoRA) is commonly applied to fine-tune large language models (LLMs). However, updati…

cs.IR2023★ 1 cited

Auto Search Indexer for End-to-End Document Retrieval

Tianchi Yang, Minghui Song, Zihan Zhang +4

Generative retrieval, which is a new advanced paradigm for document retrieval, has recently attracted research interests, since it encodes all documents into the model and directly…

cs.CL2023

Democratizing Reasoning Ability: Tailored Learning from Large Language Model

Zhaoyang Wang, Shaohan Huang, Yuxuan Liu +8

Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and cl…