Skip to content
Papers.

mHC: Manifold-Constrained Hyper-Connections research paper by DeepSeek, 2025

DeepSeek · Dec 31, 2025 · Training and scaling · 82 citations · 334 upvotes · unverified

Read on arXiv

What it shows

Manifold-Constrained Hyper-Connections (mHC) stabilize and scale residual connection architectures by restoring identity mapping properties through manifold projection and infrastructure optimization.

UnverifiedHugging Face's summary; not yet checked by hand.

More from DeepSeek

All 22
PaperCitations
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache CompressionA 552B mixture-of-experts model with a 1M-token context, built to shrink the KV cache for agent workloads.Inference and efficiency · Sep 20267
DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive GenerationDSpark enhances LLM inference speed by combining parallel draft generation with adaptive verification that reduces waste and improves throughput in high-concurrency settings.Inference and efficiency · Jul 2026 · Unverified30
DualPath: Breaking the Storage Bandwidth Bottleneck in Agentic LLM InferenceDualPath addresses KV-cache storage I/O bottlenecks in multi-turn LLM inference by introducing dual-path loading and dynamic load balancing across prefill and decode engines.Agents and evaluation · Feb 2026 · Unverified19
DeepSeek-OCR 2: Visual Causal FlowDeepSeek-OCR 2 introduces DeepEncoder V2 that dynamically reorders visual tokens based on semantic content, enabling more human-like causal reasoning in 2D image understanding through cascaded 1D causal structures.Multimodal and robotics · Jan 2026 · Unverified75
DeepSeek-V3.2: Pushing the Frontier of Open Large Language ModelsDeepSeek-V3.2 introduces DeepSeek Sparse Attention and a scalable reinforcement learning framework, achieving superior reasoning and performance compared to GPT-5 and Gemini-3.0-Pro in complex reasoning tasks.Agents and evaluation · Dec 2025 · Unverified761
DeepSeekMath-V2: Towards Self-Verifiable Mathematical ReasoningA self-verifying large language model for theorem proving improves mathematical reasoning by incentivizing rigorous step-by-step derivations and achieves high scores in international competitions.Reasoning · Nov 2025 · Unverified68
DeepSeek-OCR: Contexts Optical CompressionDeepSeek-OCR uses optical 2D mapping to compress long contexts, achieving high OCR precision with reduced vision tokens and demonstrating practical value in document processing.Inference and efficiency · Oct 2025 · Unverified189
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI ArchitecturesDeepSeek-V3 addresses hardware limitations through MLA, MoE, FP8 training, and Multi-Plane Network Topology, enabling efficient large-scale LLM training and inference.Inference and efficiency · May 2025 · Unverified107

Other training and scaling papers

Topic
PaperCitations
LoRA: Low-Rank Adaptation of Large Language ModelsLoRA fine-tunes a large model by training small low-rank matrices, cutting trainable parameters by 10,000 times.Microsoft · Jun 202123.3k
Scaling Laws for Neural Language ModelsLanguage model loss falls as a smooth power law as model size, data and compute grow.OpenAI · Jan 20209,065
Training Compute-Optimal Large Language ModelsChinchilla: for a fixed compute budget, train a smaller model on more data; parameters and tokens should grow together.Google DeepMind · Mar 20223,756
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model ParallelismMegatron-LM splits each Transformer layer across GPUs to train models with billions of parameters.NVIDIA · Sep 20193,179
LoRA Learns Less and Forgets LessLoRA learns less than full fine-tuning on code and math, but forgets less of what the model already knew.Databricks · May 2024407
jina-embeddings-v3: Multilingual Embeddings With Task LoRAjina-embeddings-v3, a large-scale text embedding model, achieves state-of-the-art performance in multilingual and long-context retrieval tasks using Low-Rank Adaptation and Matryoshka Representation Learning.Jina AI · Sep 2024 · Unverified200
About this paper
Authors
Zhenda Xie, Yixuan Wei, Huanqi Cao and 16 more
arXiv
2512.24880 · PDF
Venue
arXiv.org
Citations
82, 19 influential · Semantic Scholar
Upvotes
334 · Hugging Face
Lab
DeepSeek · on Companies

Changes

What changed
Influential citationsfirst count: 19Sep 25, 2026
Citationsfirst count: 82Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

New papers by email

Monday afternoons, only in weeks with new papers from the labs.

Double opt-in. Unsubscribe any time.