activity
20232025
most citedSpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms

1 citations · 3 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2025

Let Language Constrain Geometry: Vision-Language Models as Semantic and Spatial Critics for 3D Generation

Weimin Bai, Yubo Li, Weijian Luo +4

Text-to-3D generation has advanced rapidly, yet state-of-the-art models, encompassing both optimization-based and feed-forward architectures, still face two fundamental limitations…

cs.SD2025

FLM-Audio: Natural Monologues Improves Native Full-Duplex Chatbots via Dual Training

Yiqun Yao, Xiang Li, Xin Jiang +5

Full-duplex dialog models aim to listen and speak simultaneously, delivering rapid responses to dynamic user input. Among different solutions to full-duplexity, a native solution m…

cs.AI2025

RoboEgo System Card: An Omnimodal Model with Native Full Duplexity

Yiqun Yao, Xiang Li, Xin Jiang +4

Humans naturally process real-world multimodal information in a full-duplex manner. In artificial intelligence, replicating this capability is essential for advancing model develop…

cs.CL2025

The Price of a Second Thought: On the Evaluation of Reasoning Efficiency in Large Language Models

Siqi Fan, Bowen Qin, Peng Han +3

Recent thinking models trained with reinforcement learning and backward-checking CoT often suffer from overthinking: they produce excessively long outputs even on simple problems,…

cs.CL2025

Position-Aware Depth Decay Decoding (): Boosting Large Language Model Inference Efficiency

Siqi Fan, Xuezhi Fang, Xingrun Xing +3

Due to the large number of parameters, the inference phase of Large Language Models (LLMs) is resource-intensive. Unlike traditional model compression, which needs retraining, rece…

cs.CL2024★ 1 cited

52B to 1T: Lessons Learned via Tele-FLM Series

Xiang Li, Yiqun Yao, Xin Jiang +17

Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic…

cs.NE2024★ 1 cited

SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms

Xingrun Xing, Zheng Zhang, Ziyi Ni +6

Towards energy-efficient artificial intelligence similar to the human brain, the bio-inspired spiking neural networks (SNNs) have advantages of biological plausibility, event-drive…

cs.CL2024

Tele-FLM Technical Report

Xiang Li, Yiqun Yao, Xin Jiang +17

Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable p…

cs.LG2023★ 1 cited

BiPFT: Binary Pre-trained Foundation Transformer with Low-rank Estimation of Binarization Residual Polynomials

Xingrun Xing, Li Du, Xinyuan Wang +4

Pretrained foundation models offer substantial benefits for a wide range of downstream tasks, which can be one of the most potential techniques to access artificial general intelli…