{"total":118,"rows":[{"id":"2502.09597","title":"Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs","created":"2025-02-13","cited_by_count":148,"area":null},{"id":"2510.05381","title":"Context Length Alone Hurts LLM Performance Despite Perfect Retrieval","created":"2025-10-06","cited_by_count":127,"area":null},{"id":"2502.05167","title":"NoLiMa: Long-Context Evaluation Beyond Literal Matching","created":"2025-02-07","cited_by_count":126,"area":null},{"id":"2505.23735","title":"ATLAS: Learning to Optimally Memorize the Context at Test Time","created":"2025-05-29","cited_by_count":66,"area":null},{"id":"2511.02817","title":"Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities","created":"2025-11-04","cited_by_count":40,"area":null},{"id":"2503.04176","title":"TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records","created":"2025-03-06","cited_by_count":34,"area":null},{"id":"2505.16381","title":"PaTH Attention: Position Encoding via Accumulating Householder Transformations","created":"2025-05-22","cited_by_count":34,"area":null},{"id":"2512.17351","title":"Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers","created":"2025-12-19","cited_by_count":33,"area":null},{"id":"2411.15102","title":"AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution","created":"2024-11-22","cited_by_count":23,"area":null},{"id":"2507.02782","title":"Understanding and Improving Length Generalization in Recurrent Models","created":"2025-07-03","cited_by_count":23,"area":null},{"id":"2506.13356","title":"StoryBench: A Dynamic Benchmark for Evaluating Long-Term Memory with Multi Turns","created":"2025-06-16","cited_by_count":20,"area":null},{"id":"2503.01996","title":"One ruler to measure them all: Benchmarking multilingual long-context language models","created":"2025-03-03","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":"2602.24281","title":"Memory Caching: RNNs with Growing Memory","created":"2026-02-27","cited_by_count":15,"area":null},{"id":"2412.14140","title":"GLIDER: Grading LLM Interactions and Decisions using Explainable Ranking","created":"2024-12-18","cited_by_count":14,"area":null},{"id":"2501.13121","title":"Episodic Memories Generation and Evaluation Benchmark for Large Language Models","created":"2025-01-21","cited_by_count":14,"area":null},{"id":"2407.15176","title":"ReAttention: Training-Free Infinite Context with Finite Attention Scope","created":"2024-07-21","cited_by_count":13,"area":null},{"id":"2502.06049","title":"LM2: Large Memory Models","created":"2025-02-09","cited_by_count":13,"area":null},{"id":"2502.15007","title":"LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers","created":"2025-02-20","cited_by_count":12,"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":"2407.03841","title":"On the Benchmarking of LLMs for Open-Domain Dialogue Evaluation","created":"2024-07-04","cited_by_count":10,"area":null},{"id":"2504.00927","title":"Multi-Token Attention","created":"2025-04-01","cited_by_count":10,"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":"2508.07479","title":"Positional Biases Shift as Inputs Approach Context Window Limits","created":"2025-08-10","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":"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":"2510.10457","title":"Rethinking LLM Evaluation: Can We Evaluate LLMs with 200x Less Data?","created":"2025-10-12","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":"2505.23295","title":"How Does Response Length Affect Long-Form Factuality","created":"2025-05-29","cited_by_count":6,"area":null},{"id":"2506.00400","title":"Scaling Textual Gradients via Sampling-Based Momentum","created":"2025-05-31","cited_by_count":6,"area":null},{"id":"2510.17196","title":"Understanding and Improving Length Generalization in Hierarchical Sparse Attention Models","created":"2025-10-20","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":"2410.02115","title":"L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?","created":"2024-10-03","cited_by_count":5,"area":null},{"id":"2505.03985","title":"LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration","created":"2025-05-06","cited_by_count":5,"area":null},{"id":"2505.13757","title":"CoRank: LLM-Based Compact Reranking with Document Features for Scientific Retrieval","created":"2025-05-19","cited_by_count":5,"area":null},{"id":"2506.03426","title":"Adaptive Task Vectors for Large Language Models","created":"2025-06-03","cited_by_count":5,"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":"2510.05862","title":"Revisiting Long-context Modeling from Context Denoising Perspective","created":"2025-10-07","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":"2406.12018","title":"CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling","created":"2024-06-17","cited_by_count":4,"area":null},{"id":"2506.11769","title":"Long-Short Alignment for Effective Long-Context Modeling in LLMs","created":"2025-06-13","cited_by_count":4,"area":null},{"id":"2602.02180","title":"STILL: Selecting Tokens for Intra-Layer Hybrid Attention to Linearize LLMs","created":"2026-02-02","cited_by_count":4,"area":null},{"id":"2409.06338","title":"Retrieval Or Holistic Understanding? Dolce: Differentiate Our Long Context Evaluation Tasks","created":"2024-09-10","cited_by_count":3,"area":null},{"id":"2509.18467","title":"LAWCAT: Efficient Distillation from Quadratic to Linear Attention with Convolution across Tokens for Long Context Modeling","created":"2025-09-22","cited_by_count":3,"area":null},{"id":"2509.24563","title":"NeMo: Needle in a Montage for Video-Language Understanding","created":"2025-09-29","cited_by_count":3,"area":null},{"id":"2511.23319","title":"Every Token Counts: Generalizing 16M Ultra-Long Context in Large Language Models","created":"2025-11-28","cited_by_count":3,"area":null},{"id":"2512.19154","title":"Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments","created":"2025-12-22","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":"2603.17484","title":"Learning When to Attend: Conditional Memory Access for Long-Context LLMs","created":"2026-03-18","cited_by_count":3,"area":null},{"id":"2605.30260","title":"How LoRA Remembers? A Parametric Memory Law for LLM Finetuning","created":"2026-05-28","cited_by_count":3,"area":null},{"id":"2407.13481","title":"Attention Overflow: Language Model Input Blur during Long-Context Missing Items Recommendation","created":"2024-07-18","cited_by_count":2,"area":null},{"id":"2411.15993","title":"Investigating Factuality in Long-Form Text Generation: The Roles of Self-Known and Self-Unknown","created":"2024-11-24","cited_by_count":2,"area":null},{"id":"2505.08651","title":"Scaling Context, Not Parameters: Training a Compact 7B Language Model for Efficient Long-Context Processing","created":"2025-05-13","cited_by_count":2,"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":"2506.05229","title":"Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts","created":"2025-06-05","cited_by_count":2,"area":null},{"id":"2507.09506","title":"Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models","created":"2025-07-13","cited_by_count":2,"area":null},{"id":"2511.03718","title":"Grounded Misunderstandings in Asymmetric Dialogue: A Perspectivist Annotation Scheme for MapTask","created":"2025-11-05","cited_by_count":2,"area":null},{"id":"2512.07525","title":"Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs","created":"2025-12-08","cited_by_count":2,"area":null},{"id":"2603.16120","title":"Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users","created":"2026-03-17","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":"2604.07737","title":"SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs","created":"2026-04-09","cited_by_count":2,"area":null},{"id":"2605.06142","title":"IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences","created":"2026-05-07","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":"2606.03979","title":"Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories","created":"2026-06-02","cited_by_count":2,"area":null},{"id":"2606.05008","title":"M$^3$Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks","created":"2026-06-03","cited_by_count":2,"area":null},{"id":"2608.01672","title":"Learning What to Remember: Test-Time Training via Context Distillation","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2407.12833","title":"ESQA: Event Sequences Question Answering","created":"2024-07-03","cited_by_count":1,"area":null},{"id":"2408.02439","title":"Long Input Benchmark for Russian Analysis","created":"2024-08-05","cited_by_count":1,"area":null},{"id":"2501.09166","title":"Attention is All You Need Until You Need Retention","created":"2025-01-15","cited_by_count":1,"area":null},{"id":"2504.08202","title":"Harnessing the Unseen: The Hidden Influence of Intrinsic Knowledge in Long-Context Language Models","created":"2025-04-11","cited_by_count":1,"area":null},{"id":"2505.20195","title":"Monocle: Hybrid Local-Global In-Context Evaluation for Long-Text Generation with Uncertainty-Based Active Learning","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2506.12189","title":"Supernova Event Dataset: Interpreting Large Language Models' Personality through Critical Event Analysis","created":"2025-06-13","cited_by_count":1,"area":null},{"id":"2506.14407","title":"ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge","created":"2025-06-17","cited_by_count":1,"area":null},{"id":"2507.12442","title":"Characterizing State Space Model and Hybrid Language Model Performance with Long Context","created":"2025-07-16","cited_by_count":1,"area":null},{"id":"2602.10410","title":"LUCID: Attention with Preconditioned Representations","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2604.05438","title":"Residual-Mass Accounting for Partial-KV Decoding","created":"2026-04-07","cited_by_count":1,"area":null},{"id":"2605.30628","title":"The Architecture of Errors: From Universal Impossibility to Patch-Local LLM Reliability","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2606.25156","title":"ATMA: Long-Context Language Modeling via Polar Attention and Gated-Delta Compression Memory","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2607.28263","title":"CoMem: Reusing Transformer Depth across Queries with Persistent Intermediate Residuals","created":"2026-07-30","cited_by_count":1,"area":null},{"id":"2608.16844","title":"Proteus: Incremental Memory Activation for Long-Context Sequence Modeling","created":"2026-08-17","cited_by_count":1,"area":null},{"id":"2502.15872","title":"MutaGReP: Execution-Free Repository-Grounded Plan Search for Code-Use","created":"2025-02-21","cited_by_count":0,"area":null},{"id":"2503.13562","title":"Detecting Scarce and Sparse Anomalous: Solving Dual Imbalance in Multi-Instance Learning","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2507.16271","title":"Beyond Isolated Dots: Benchmarking Structured Table Construction as Deep Knowledge Extraction","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2507.22411","title":"NeedleChain: Measuring Intact Context Comprehension Capability of Large Language Models","created":"2025-07-30","cited_by_count":0,"area":null},{"id":"2510.05864","title":"On the Sensitivity of Instruction-tuned LLMs to Harmful Sentences in Long Inputs","created":"2025-10-07","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":"2601.11468","title":"Exploring LLM Features in Predictive Process Monitoring for Small-Scale Event-Logs","created":"2026-01-16","cited_by_count":0,"area":null},{"id":"2601.12410","title":"Are LLMs Smarter Than Chimpanzees? An Evaluation on Perspective Taking and Knowledge State Estimation","created":"2026-01-18","cited_by_count":0,"area":null},{"id":"2601.13734","title":"Towards robust long-context understanding of large language model via active recap learning","created":"2026-01-20","cited_by_count":0,"area":null},{"id":"2605.09932","title":"FocuSFT: Bilevel Optimization for Dilution-Aware Long-Context Fine-Tuning","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2605.10339","title":"An Annotation Scheme and Classifier for Personal Facts in Dialogue","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2605.13438","title":"CogniFold: Always-On Proactive Memory via Cognitive Folding","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2606.00132","title":"Foundation-Preserving Optimization in Generalized Eigenspace","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.05646","title":"Enhancing Software Engineering Through Closed-Loop Memory Optimization","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2606.06203","title":"Dense Contexts Are Hard Contexts: Lexical Density Limits Effective Context in LLMs","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2607.01002","title":"Logit-Contribution Scoring Identifies Non-Literal Retrieval Heads","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2607.09328","title":"WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning","created":"2026-07-10","cited_by_count":0,"area":null},{"id":"2607.11614","title":"Extending LLM Context via Associative Recurrent Memory","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2607.20457","title":"Dropping the Anchor: Statistical Context Summarization for Distributed Systems via Pulsar Attention","created":"2026-05-14","cited_by_count":0,"area":null}],"next_cursor":"100"}