EndPrompt: Efficient Long-Context Extension via Terminal Anchoring research paper by Baidu, 2026

Baidu · Inference and efficiency · May 14, 2026 · 0 citations · 15 upvotes · unverified

EndPrompt extends large language model context windows by using a two-segment training approach that preserves semantic continuity while enabling efficient long-range positional learning through sparse supervision.

By Han Tian, Luxuan Chen, Xinran Chen and 9 more · arXiv 2605.14589 · PDF · Code

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

More from Baidu

All 16

Inference and efficiencyUnverifiedOct 13, 2026FlashMask-3: Efficient and Expressive Mask-Aware Distributed AttentionFlashMask-3 accelerates long-context attention via a Hopper-optimized sparse-mask kernel and distributed context-parallel extensions that eliminate mask-communication overhead and improve training throughput.

Baidu11 upvotesRead →Inference and efficiencyUnverifiedOct 13, 2026Virtual Head AttentionVirtual Head Attention improves long-context model efficiency by reducing KV cache and compute while preserving quality through lightweight linear query and output transformations.

Baidu17 upvotesRead →Inference and efficiencyUnverifiedJun 22, 2026Unlimited OCR WorksUnlimited OCR introduces Reference Sliding Window Attention to eliminate growing memory consumption during long-sequence OCR tasks, enabling efficient transcription of multiple pages in a single forward pass.

Baidu9 citations90 upvotesRead →Multimodal and roboticsUnverifiedJun 12, 2026Memento: Reconstruct to Remember for Consistent Long Video GenerationMemento is a subject-reconstruction-guided framework that improves long-form video generation by preserving recurring subjects through memory-based reconstruction and dual-query mechanisms.

Baidu6 citations18 upvotesRead →Agents and evaluationUnverifiedJun 5, 2026DuMate-DeepResearch: An Auditable Multi-Agent System with Recursive Search and Rubric-Grounded ReasoningA multi-agent framework for deep research tasks that addresses planning, evidence acquisition, and report synthesis through decoupled components and dynamic optimization mechanisms.

Baidu2 citations9 upvotesRead →Agents and evaluationUnverifiedJun 4, 2026When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM AgentsToolMaze benchmark reveals that real-world tool failures significantly degrade TIR performance, with implicit semantic failures causing the most severe drops and dynamic replanning emerging as a key bottleneck.

Baidu28 citations27 upvotesRead →Agents and evaluationUnverifiedJun 3, 2026MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map GenerationMapAgent is an industrial-grade agentic architecture that combines vision-language processing with constraint-aware reasoning to produce specification-compliant lane maps, achieving high automation rates in large-scale urban mapping.

Baidu2 citations18 upvotesRead →Alignment and safetyUnverifiedMay 28, 2026Native Audio-Visual Alignment for GenerationNAVA enables joint audio-video generation with improved synchronization and controllability through native audio-visual alignment and context-conditioned denoising.

Baidu8 citations31 upvotesRead →

Topic

Inference and efficiencySep 12, 2023Efficient Memory Management for Large Language Model Serving with PagedAttentionvLLM manages the KV cache like pages of virtual memory, serving models with 2 to 4 times the throughput.

UC Berkeley9,965 citations72 upvotesRead →Inference and efficiencyMay 27, 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-AwarenessFlashAttention computes exact attention with far fewer GPU memory reads and writes, making long sequences faster.

Stanford University5,830 citations16 upvotesRead →Inference and efficiencyUnverifiedJul 24, 2025Group Sequence Policy OptimizationGroup Sequence Policy Optimization (GSPO) is a reinforcement learning algorithm that improves training efficiency and performance of large language models by using sequence-level importance ratios and operations.

Alibaba (Qwen)814 citations323 upvotesRead →Inference and efficiencyUnverifiedFeb 16, 2025Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse AttentionNSA, a trainable sparse attention mechanism, enhances long-context modeling efficiency without sacrificing performance, achieving improvements in speed and accuracy over full attention models.

DeepSeek596 citations157 upvotesRead →Inference and efficiencyUnverifiedApr 7, 2025SmolVLM: Redefining small and efficient multimodal modelsSmolVLM, a series of compact multimodal models, achieves high performance with minimal GPU memory usage, making efficient deployment on mobile and edge devices possible.

Hugging Face330 citations212 upvotesRead →Inference and efficiencyUnverifiedOct 17, 2025Chronos-2: From Univariate to Universal ForecastingChronos-2, a pretrained model with a group attention mechanism, achieves state-of-the-art performance in zero-shot univariate, multivariate, and covariate-informed forecasting tasks.

Amazon276 citations28 upvotesRead →

About this paper

Venue: arXiv.org
Citations: 0, 0 influential · Semantic Scholar
Upvotes: 15 · Hugging Face
Lab: Baidu · on Companies · on Quarterly

Changes

CitationsNov 9, 2026A first count of 0 influential citations.

CitationsNov 9, 2026A first count of 0 citations.

New paperNov 9, 2026Found by the weekly Hugging Face scan; not yet checked by hand.

What it shows

More from Baidu

Other inference and efficiency papers

Changes