3 citations · 11 across the 19 of their papers we have counts for
10 papers · 1 filter
DePass: Unified Feature Attributing by Simple Decomposed Forward Pass
Xiangyu Hong, Che Jiang, Kai Tian +4
Attributing the behavior of Transformer models to internal computations is a central challenge in mechanistic interpretability. We introduce DePass, a unified framework for feature…
ShapeCraft: LLM Agents for Structured, Textured and Interactive 3D Modeling
Shuyuan Zhang, Chenhan Jiang, Zuoou Li +1
3D generation from natural language offers significant potential to reduce expert manual modeling efforts and enhance accessibility to 3D assets. However, existing methods often yi…
A Survey of Reinforcement Learning for Large Reasoning Models
Kaiyan Zhang, Yuxin Zuo, Bingxiang He +36
In this paper, we survey recent advances in Reinforcement Learning (RL) for reasoning with Large Language Models (LLMs). RL has achieved remarkable success in advancing the frontie…
Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism
Yuhua Jiang, Shuang Cheng, Yihao Liu +7
Large Language Models (LLMs) excel at general language tasks but struggle in specialized domains. Specialized Generalist Models (SGMs) address this by preserving broad capabilities…
AdsQA: Towards Advertisement Video Understanding
Xinwei Long, Kai Tian, Peng Xu +10
Large language models (LLMs) have taken a great step towards AGI. Meanwhile, an increasing number of domain-specific problems such as math and programming boost these general-purpo…
FlowRL: Matching Reward Distributions for LLM Reasoning
Xuekai Zhu, Daixuan Cheng, Dinghuai Zhang +20
We propose FlowRL: matching the full reward distribution via flow balancing instead of maximizing rewards in large language model (LLM) reinforcement learning (RL). Recent advanced…
SSRL: Self-Search Reinforcement Learning
Yuchen Fan, Kaiyan Zhang, Heng Zhou +15
We investigate the potential of large language models (LLMs) to serve as efficient simulators for agentic search tasks in reinforcement learning (RL), thereby reducing dependence o…
Context-Aware Autoregressive Models for Multi-Conditional Image Generation
Yixiao Chen, Zhiyuan Ma, Guoli Jia +3
Autoregressive transformers have recently shown impressive image generation quality and efficiency on par with state-of-the-art diffusion models. Unlike diffusion architectures, au…
WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation
Daoan Zhang, Che Jiang, Ruoshi Xu +7
Recent text-to-image (T2I) models achieve high visual fidelity and accurate explicit grounding from input prompts. However, image generation is fundamentally a process of semantic…
Seesaw: High-throughput LLM Inference via Model Re-sharding
Qidong Su, Wei Zhao, Xin Li +6
To improve the efficiency of distributed large language model (LLM) inference, various parallelization strategies, such as tensor and pipeline parallelism, have been proposed. Howe…