activity
20242026
collaborators

10 papers

cs.CL2026

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

DeepSeek-AI, :, Anyi Xu +585

The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…

cs.CL2026

Revisiting Lossy Verification in Speculative Decoding: Mechanisms, Trade-offs, and Failure Modes

Tianyu Wang, Yuxuan Zhou, Heng Li +4

Speculative Decoding (SD) accelerates large language model inference by allowing a lightweight draft model to propose tokens that are subsequently verified in parallel by a larger…

cs.RO2026

Plan Right, Then Plan Tight: Symbolic RL for Efficient Embodied Reasoning

Xiangli Shi, Xiaomeng Zhu, Ye Tian +5

Embodied task planning asks an agent to turn a natural-language instruction into an executable sequence of actions in a physical scene, and is a building block for household, assis…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.AI2026

Overcoming Joint Intractability with Lossless Hierarchical Speculative Decoding

Yuxuan Zhou, Fei Huang, Heng Li +5

Verification is a key bottleneck in improving inference speed while maintaining distribution fidelity in Speculative Decoding. Recent work has shown that sequence-level verificatio…

cs.CL2025

LongWeave: A Long-Form Generation Benchmark Bridging Real-World Relevance and Verifiability

Zikai Xiao, Fei Huang, Jianhong Tu +7

Generating long, informative, and factual outputs remains a major challenge for Large Language Models (LLMs). Existing benchmarks for long-form generation typically assess real-wor…

cs.AI2025

Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

Yifei Dong, Fengyi Wu, Guangyu Chen +9

Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typically rely on modular designs that…

cs.AI2025

HA-VLN 2.0: An Open Benchmark and Leaderboard for Human-Aware Navigation in Discrete and Continuous Environments with Dynamic Multi-Human Interactions

Yifei Dong, Fengyi Wu, Qi He +9

Vision-and-Language Navigation (VLN) has been studied mainly in either discrete or continuous spaces, with little attention to dynamic, crowded environments. We present HA-VLN 2.0,…

cs.LG2025

MaxSup: Overcoming Representation Collapse in Label Smoothing

Yuxuan Zhou, Heng Li, Zhi-Qi Cheng +4

Label Smoothing (LS) is widely adopted to reduce overconfidence in neural network predictions and improve generalization. Despite these benefits, recent studies reveal two critical…

cs.AI2024

Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions

Heng Li, Minghan Li, Zhi-Qi Cheng +6

Vision-and-Language Navigation (VLN) aims to develop embodied agents that navigate based on human instructions. However, current VLN frameworks often rely on static environments an…