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Jinyu Wang

7 accepted papers

2026

3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis

ICML 2026poster

3D CT analysis spans a continuum from low-level perception to high-level clinical understanding. Existing 3D-oriented analysis methods adopt either isolated task-specific modeling or task-agnostic end-to-end paradigms to produce one-hop outputs, impeding the systematic accumulation of perceptual evi…

Cited by 2SourceScholar
2026

In-Context Compositional Q-Learning for Offline Reinforcement Learning

ICLR 2026poster

Accurately estimating the Q-function is a central challenge in offline reinforcement learning. However, existing approaches often rely on a single global Q-function, which struggles to capture the compositional nature of tasks involving diverse subtasks. We propose In-context Compositional Q-Learnin…

Cited by 0SourceScholar
2026

KVmix: Gradient-Based Layer Importance-Aware Mixed-Precision Quantization for KV Cache

AAAI 2026technical

The high memory demands of the Key-Value (KV) Cache during the inference of Large Language Models (LLMs) severely restrict their deployment in resource-constrained platforms. Quantization can effectively alleviate the memory pressure caused by KV Cache. However, existing methods either rely on stati

Cited by 0SourcePDFScholar
2025

From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning

ICML 2025poster

Recent advancements in Retrieval-Augmented Generation (RAG) systems have significantly enhanced the capabilities of large language models (LLMs) by incorporating external knowledge retrieval. However, the sole reliance on retrieval is often inadequate for mining deep, domain-specific knowledge and f…

Cited by 0SourcePDFScholar
2025

OMGM: Orchestrate Multiple Granularities and Modalities for Efficient Multimodal Retrieval

ACL 2025long

Vision-language retrieval-augmented generation (RAG) has become an effective approach for tackling Knowledge-Based Visual Question Answering (KB-VQA), which requires external knowledge beyond the visual content presented in images. The effectiveness of Vision-language RAG systems hinges on multimoda…

2025

Unveiling Markov heads in Pretrained Language Models for Offline Reinforcement Learning

ICML 2025poster

Recently, incorporating knowledge from pretrained language models (PLMs) into decision transformers (DTs) has generated significant attention in offline reinforcement learning (RL). These PLMs perform well in RL tasks, raising an intriguing question: what kind of knowledge from PLMs has been transfe…

Cited by 0SourcePDFScholar
2024

Protecting Your LLMs with Information Bottleneck

NeurIPS 2024poster

The advent of large language models (LLMs) has revolutionized the field of natural language processing, yet they might be attacked to produce harmful content. Despite efforts to ethically align LLMs, these are often fragile and can be circumvented by jailbreaking attacks through optimized or manual…