{"total":163,"rows":[{"id":"2511.02817","title":"Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities","created":"2025-11-04","cited_by_count":40,"area":null},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2510.23081","title":"A Survey on LLM Mid-Training","created":"2025-10-27","cited_by_count":21,"area":null},{"id":"2501.12766","title":"NExtLong: Toward Effective Long-Context Training without Long Documents","created":"2025-01-22","cited_by_count":20,"area":null},{"id":"2601.02872","title":"LongBench Pro: A More Realistic and Comprehensive Bilingual Long-Context Evaluation Benchmark","created":"2026-01-06","cited_by_count":19,"area":null},{"id":"2508.04664","title":"Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management","created":"2025-08-06","cited_by_count":18,"area":null},{"id":"2601.20251","title":"Efficient Evaluation of LLM Performance with Statistical Guarantees","created":"2026-01-28","cited_by_count":18,"area":null},{"id":"2503.04723","title":"Shifting Long-Context LLMs Research from Input to Output","created":"2025-03-06","cited_by_count":14,"area":null},{"id":"2512.12087","title":"BLASST: Dynamic BLocked Attention Sparsity via Softmax Thresholding","created":"2025-12-12","cited_by_count":13,"area":null},{"id":"2603.01097","title":"Understanding LoRA as Knowledge Memory: An Empirical Analysis","created":"2026-03-01","cited_by_count":12,"area":null},{"id":"2509.24552","title":"Short window attention enables long-term memorization","created":"2025-09-29","cited_by_count":11,"area":null},{"id":"2510.07318","title":"Artificial Hippocampus Networks for Efficient Long-Context Modeling","created":"2025-10-08","cited_by_count":11,"area":null},{"id":"2502.16860","title":"LongAttn: Selecting Long-context Training Data via Token-level Attention","created":"2025-02-24","cited_by_count":9,"area":null},{"id":"2504.16795","title":"Hardware-aligned Hierarchical Sparse Attention for Efficient Long-term Memory Access","created":"2025-04-23","cited_by_count":9,"area":null},{"id":"2506.16411","title":"When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework","created":"2025-06-19","cited_by_count":9,"area":null},{"id":"2509.24745","title":"ProxyAttn: Guided Sparse Attention via Representative Heads","created":"2025-09-29","cited_by_count":9,"area":null},{"id":"2602.12108","title":"The Pensieve Paradigm: Stateful Language Models Mastering Their Own Context","created":"2026-02-12","cited_by_count":9,"area":null},{"id":"2604.27043","title":"CL-bench Life: Can Language Models Learn from Real-Life Context?","created":"2026-04-29","cited_by_count":9,"area":null},{"id":"2605.26302","title":"Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems","created":"2026-05-25","cited_by_count":9,"area":null},{"id":"2504.06560","title":"NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables","created":"2025-04-09","cited_by_count":8,"area":null},{"id":"2505.19959","title":"MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models","created":"2025-05-26","cited_by_count":8,"area":null},{"id":"2510.22548","title":"LooGLE v2: Are LLMs Ready for Real World Long Dependency Challenges?","created":"2025-10-26","cited_by_count":8,"area":null},{"id":"2601.05505","title":"FlashMem: Distilling Intrinsic Latent Memory via Computation Reuse","created":"2026-01-09","cited_by_count":8,"area":null},{"id":"2506.02921","title":"A Controllable Examination for Long-Context Language Models","created":"2025-06-03","cited_by_count":7,"area":null},{"id":"2505.17134","title":"LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions","created":"2025-05-22","cited_by_count":6,"area":null},{"id":"2510.13494","title":"LiteraryQA: Towards Effective Evaluation of Long-document Narrative QA","created":"2025-10-15","cited_by_count":6,"area":null},{"id":"2510.20941","title":"Do LLMs Truly Understand When a Precedent Is Overruled?","created":"2025-10-23","cited_by_count":6,"area":null},{"id":"2512.23966","title":"Efficient Context Scaling with LongCat ZigZag Attention","created":"2025-12-30","cited_by_count":6,"area":null},{"id":"2601.07023","title":"CloneMem: Benchmarking Long-Term Memory for AI Clones","created":"2026-01-11","cited_by_count":6,"area":null},{"id":"2603.05890","title":"Lost in Stories: Consistency Bugs in Long Story Generation by LLMs","created":"2026-03-06","cited_by_count":6,"area":null},{"id":"2605.19577","title":"GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment","created":"2026-05-19","cited_by_count":6,"area":null},{"id":"2507.04723","title":"LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework","created":"2025-07-07","cited_by_count":5,"area":null},{"id":"2510.02330","title":"EntropyLong: Effective Long-Context Training via Predictive Uncertainty","created":"2025-09-26","cited_by_count":5,"area":null},{"id":"2510.05862","title":"Revisiting Long-context Modeling from Context Denoising Perspective","created":"2025-10-07","cited_by_count":5,"area":null},{"id":"2510.21270","title":"Sparser Block-Sparse Attention via Token Permutation","created":"2025-10-24","cited_by_count":5,"area":null},{"id":"2601.17367","title":"Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers","created":"2026-01-24","cited_by_count":5,"area":null},{"id":"2603.07392","title":"Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams","created":"2026-03-08","cited_by_count":5,"area":null},{"id":"2505.10063","title":"CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability","created":"2025-05-15","cited_by_count":4,"area":null},{"id":"2506.16024","title":"From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation","created":"2025-06-19","cited_by_count":4,"area":null},{"id":"2512.10411","title":"SWAA: Sliding Window Attention Adaptation for Efficient and Quality Preserving Long Context Processing","created":"2025-12-11","cited_by_count":4,"area":null},{"id":"2512.17452","title":"KV Admission: Learning What to Write for Efficient Long-Context LLM Inference","created":"2025-12-19","cited_by_count":4,"area":null},{"id":"2601.22181","title":"MrRoPE: Mixed-radix Rotary Position Embedding","created":"2026-01-28","cited_by_count":4,"area":null},{"id":"2602.17431","title":"Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study","created":"2026-02-19","cited_by_count":4,"area":null},{"id":"2606.26453","title":"Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization","created":"2026-06-24","cited_by_count":4,"area":null},{"id":"2607.22566","title":"MedLoCoMo: A Long-Context Multi-Session Medical Dialogue Benchmark for Large Language Models","created":"2026-05-31","cited_by_count":4,"area":null},{"id":"2505.22842","title":"Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation","created":"2025-05-28","cited_by_count":3,"area":null},{"id":"2512.03494","title":"A Preliminary Study on the Promises and Challenges of Native Top-$k$ Sparse Attention","created":"2025-12-03","cited_by_count":3,"area":null},{"id":"2602.01075","title":"ConvexBench: Can LLMs Recognize Convex Functions?","created":"2026-02-01","cited_by_count":3,"area":null},{"id":"2602.23061","title":"MoDora: Tree-Based Semi-Structured Document Analysis System","created":"2026-02-26","cited_by_count":3,"area":null},{"id":"2603.06610","title":"CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training","created":"2026-02-19","cited_by_count":3,"area":null},{"id":"2604.06111","title":"AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments","created":"2026-04-07","cited_by_count":3,"area":null},{"id":"2505.13353","title":"Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2507.19786","title":"Flora: Effortless Context Construction to Arbitrary Length and Scale","created":"2025-07-26","cited_by_count":2,"area":null},{"id":"2509.08016","title":"Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs","created":"2025-09-09","cited_by_count":2,"area":null},{"id":"2510.10549","title":"ELAIPBench: A Benchmark for Expert-Level Artificial Intelligence Paper Understanding","created":"2025-10-12","cited_by_count":2,"area":null},{"id":"2602.05712","title":"Towards Green AI: Decoding the Energy of LLM Inference in Software Development","created":"2026-02-05","cited_by_count":2,"area":null},{"id":"2602.09075","title":"Learning to Remember, Learn, and Forget in Attention-Based Models","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2602.22175","title":"DySCO: Dynamic Attention-Scaling Decoding for Long-Context Language Models","created":"2026-02-25","cited_by_count":2,"area":null},{"id":"2603.04857","title":"FireBench: Evaluating Instruction Following in Enterprise and API-Driven LLM Applications","created":"2026-03-05","cited_by_count":2,"area":null},{"id":"2603.15653","title":"Recursive Language Models Meet Uncertainty: The Surprising Effectiveness of Self-Reflective Program Search for Long Context","created":"2026-03-07","cited_by_count":2,"area":null},{"id":"2603.22608","title":"Understanding LLM Performance Degradation in Multi-Instance Processing: The Roles of Instance Count and Context Length","created":"2026-03-23","cited_by_count":2,"area":null},{"id":"2605.07076","title":"Self-Consolidating Language Models: Continual Knowledge Incorporation from Context","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2605.28079","title":"ATLAS: All-round Testing of Long-context Abilities across Scales","created":"2026-05-27","cited_by_count":2,"area":null},{"id":"2605.31086","title":"Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory","created":"2026-05-29","cited_by_count":2,"area":null},{"id":"2606.21803","title":"Test-Time Training with Next-Token Prediction","created":"2026-06-19","cited_by_count":2,"area":null},{"id":"2607.01538","title":"Can Language Models Actually Retrieve In-Context? Drowning in Documents at Million Token Scale","created":"2026-07-01","cited_by_count":2,"area":null},{"id":"2608.01662","title":"LongCat Sparse Attention: Taming the Lightning via Streaming-aware Hierarchical Cross-Layer Indexing","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2608.12435","title":"MARCH: Scaling Recurrent Memory with Content-Routed State Anchors","created":"2026-08-12","cited_by_count":2,"area":null},{"id":"2609.22452","title":"Vox-Infinity: Benchmarking the Limits of Long-Context Spoken Language Models","created":"2026-09-18","cited_by_count":2,"area":null},{"id":"2504.14366","title":"What Matters in Linearizing Language Models? A Comparative Study of Architecture, Scale, and Task Adaptation","created":"2025-04-19","cited_by_count":1,"area":null},{"id":"2505.17296","title":"SELF: Self-Extend the Context Length With Logistic Growth Function","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2511.04952","title":"LoPT: Lossless Parallel Tokenization Acceleration for Long Context Inference of Large Language Model","created":"2025-11-07","cited_by_count":1,"area":null},{"id":"2602.16704","title":"Reinforced Fast Weights with Next-Sequence Prediction","created":"2026-02-18","cited_by_count":1,"area":null},{"id":"2602.22575","title":"S2O: Early Stopping for Sparse Attention via Online Permutation","created":"2026-02-26","cited_by_count":1,"area":null},{"id":"2603.05225","title":"AI+HW 2035: Shaping the Next Decade","created":"2026-03-05","cited_by_count":1,"area":null},{"id":"2604.02650","title":"Revealing the Learning Dynamics of Long-Context Continual Pre-training","created":"2026-04-03","cited_by_count":1,"area":null},{"id":"2605.04496","title":"SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2605.11744","title":"Training-Inference Consistent Segmented Execution for Long-Context LLMs","created":"2026-05-12","cited_by_count":1,"area":null},{"id":"2605.29630","title":"Entity-Collision: A Stratified Protocol for Attributing Retrieval Lift in Agent Memory","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2606.04660","title":"LifeSide: Benchmarking Agents as Lifelong Digital Companions","created":"2026-06-03","cited_by_count":1,"area":null},{"id":"2606.07703","title":"How Much Dense Attention is Necessary? Oracle-Guided Sparse Prefill for Full/GQA Layers in Hybrid Long-Context Models","created":"2026-06-05","cited_by_count":1,"area":null},{"id":"2606.09046","title":"Measurement Under Selection: Decoy-Calibrated Failure Audits for Language Models","created":"2026-06-08","cited_by_count":1,"area":null},{"id":"2606.18728","title":"LegalWorld: A Life-Cycle Interactive Environment for Legal Agents","created":"2026-06-17","cited_by_count":1,"area":null},{"id":"2606.19857","title":"Large Language Models Do Not Always Need Readable Language","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2607.02073","title":"Evidence-State Rewards for Long-Context Reasoning","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2607.09172","title":"Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations","created":"2026-07-10","cited_by_count":1,"area":null},{"id":"2607.09415","title":"Self-Guided Test-Time Training for Long-Context LLMs","created":"2026-07-10","cited_by_count":1,"area":null},{"id":"2607.25294","title":"CLBench-V: Evaluating Multimodal Context Learning from Grounding to Knowledge Acquisition","created":"2026-07-28","cited_by_count":1,"area":null},{"id":"2608.11242","title":"Lost in Context Compaction: When LLM Systems Drop Side Constraints","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2608.13966","title":"QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction","created":"2026-08-14","cited_by_count":1,"area":null},{"id":"2609.00092","title":"Safin-1: Safety from Within through Memory-Native State Evolution","created":"2026-08-31","cited_by_count":1,"area":null},{"id":"2609.14168","title":"Towards Evolving Context Parameterization for Large Language Models","created":"2026-09-12","cited_by_count":1,"area":null},{"id":"2506.04907","title":"Context Is Not Comprehension","created":"2025-06-05","cited_by_count":0,"area":null},{"id":"2508.20778","title":"SEAL: Structure and Element Aware Learning to Improve Long Structured Document Retrieval","created":"2025-08-28","cited_by_count":0,"area":null},{"id":"2510.06847","title":"OpenJAI-v1.0: An Open Thai Large Language Model","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2510.10216","title":"Learning to Guarantee Type Correctness in Code Generation through Type-Guided Program Synthesis","created":"2025-10-11","cited_by_count":0,"area":null},{"id":"2510.18691","title":"Investigating LLM Capabilities on Long Context Comprehension for Medical Question Answering","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2601.03417","title":"Implicit Graph, Explicit Retrieval: Towards Efficient and Interpretable Long-horizon Memory for Large Language Models","created":"2026-01-06","cited_by_count":0,"area":null},{"id":"2601.09723","title":"SagaScale: A Realistic, Scalable, and High-Quality Long-Context Benchmark Built from Full-Length Novels","created":"2025-12-27","cited_by_count":0,"area":null},{"id":"2602.08237","title":"Document Reconstruction Unlocks Scalable Long-Context RLVR","created":"2026-02-09","cited_by_count":0,"area":null}],"next_cursor":"100"}