{"total":65,"rows":[{"id":"2502.01951","title":"On the Emergence of Position Bias in Transformers","created":"2025-02-04","cited_by_count":59,"area":null},{"id":"2502.11371","title":"RAG vs. GraphRAG: A Systematic Evaluation and Key Insights","created":"2025-02-17","cited_by_count":53,"area":"rag"},{"id":"2601.14004","title":"Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models","created":"2026-01-20","cited_by_count":27,"area":"mechinterp"},{"id":"2503.13792","title":"Identifying and Mitigating Position Bias of Multi-image Vision-Language Models","created":"2025-03-18","cited_by_count":25,"area":"mllm"},{"id":"2510.08510","title":"To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models","created":"2025-10-09","cited_by_count":20,"area":"mllm"},{"id":"2602.13110","title":"SCOPE: Selective Conformal Optimized Pairwise LLM Judging","created":"2026-02-13","cited_by_count":14,"area":null},{"id":"2505.16415","title":"Attributing Response to Context: A Jensen-Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation","created":"2025-05-22","cited_by_count":12,"area":"rag"},{"id":"2411.05195","title":"Exploring How Generative MLLMs Perceive More Than CLIP with the Same Vision Encoder","created":"2024-11-07","cited_by_count":11,"area":"lr"},{"id":"2505.19477","title":"Judging with Many Minds: Do More Perspectives Mean Less Prejudice? On Bias Amplifications and Resistance in Multi-Agent Based LLM-as-Judge","created":"2025-05-26","cited_by_count":11,"area":"agents"},{"id":"2510.00307","title":"BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models","created":"2025-09-30","cited_by_count":11,"area":null},{"id":"2602.14233","title":"Evaluating LLMs in Finance Requires Explicit Bias Consideration","created":"2026-02-15","cited_by_count":11,"area":null},{"id":"2508.15709","title":"Position Bias Mitigates Position Bias:Mitigate Position Bias Through Inter-Position Knowledge Distillation","created":"2025-08-21","cited_by_count":9,"area":"distill"},{"id":"2510.10276","title":"Lost in the Middle: An Emergent Property from Information Retrieval Demands in LLMs","created":"2025-10-11","cited_by_count":9,"area":null},{"id":"2412.10684","title":"Inference Scaling for Bridging Retrieval and Augmented Generation","created":"2024-12-14","cited_by_count":7,"area":"rag"},{"id":"2506.07334","title":"Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models","created":"2025-06-09","cited_by_count":6,"area":"inference"},{"id":"2410.08458","title":"Simultaneous Reward Distillation and Preference Learning: Get You a Language Model Who Can Do Both","created":"2024-10-11","cited_by_count":5,"area":"alignment"},{"id":"2502.14409","title":"Unstructured Evidence Attribution for Long Context Query Focused Summarization","created":"2025-02-20","cited_by_count":5,"area":null},{"id":"2505.16134","title":"Beyond Early-Token Bias: Model-Specific and Language-Specific Position Effects in Multilingual LLMs","created":"2025-05-22","cited_by_count":5,"area":null},{"id":"2507.13949","title":"Exploiting Primacy Effect To Improve Large Language Models","created":"2025-07-18","cited_by_count":5,"area":null},{"id":"2508.03668","title":"CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction","created":"2025-08-05","cited_by_count":4,"area":null},{"id":"2410.03062","title":"Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks","created":"2024-10-04","cited_by_count":3,"area":"lr"},{"id":"2501.00257","title":"EQUATOR: A Deterministic Framework for Evaluating LLM Reasoning with Open-Ended Questions. # v1.0.0-beta","created":"2024-12-31","cited_by_count":3,"area":"lr"},{"id":"2502.08662","title":"RoToR: Towards More Reliable Responses for Order-Invariant Inputs","created":"2025-02-10","cited_by_count":3,"area":null},{"id":"2505.05026","title":"Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for Multimodal UI/UX Design Understanding","created":"2025-05-08","cited_by_count":3,"area":null},{"id":"2510.12251","title":"DSAS: A Universal Plug-and-Play Framework for Attention Optimization in Multi-Document Question Answering","created":"2025-10-14","cited_by_count":3,"area":null},{"id":"2510.26510","title":"LLMs as In-Context Meta-Learners for Model and Hyperparameter Selection","created":"2025-10-30","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":"2601.12499","title":"Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck","created":"2026-01-18","cited_by_count":3,"area":"lr"},{"id":"2603.01204","title":"Subliminal Signals in Preference Labels","created":"2026-03-01","cited_by_count":3,"area":"alignment"},{"id":"2603.21016","title":"Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO","created":"2026-03-22","cited_by_count":3,"area":"lr"},{"id":"2604.28078","title":"AesRM: Improving Video Aesthetics with Expert-Level Feedback","created":"2026-04-30","cited_by_count":3,"area":null},{"id":"2501.13833","title":"On the Reasoning Capacity of AI Models and How to Quantify It","created":"2025-01-23","cited_by_count":2,"area":"lr"},{"id":"2503.13305","title":"Computation Mechanism Behind LLM Position Generalization","created":"2025-03-17","cited_by_count":2,"area":null},{"id":"2506.15925","title":"Reranking-based Generation for Unbiased Perspective Summarization","created":"2025-06-19","cited_by_count":2,"area":null},{"id":"2509.21984","title":"Beyond the Vision Encoder: Identifying and Mitigating Spatial Bias in Large Vision-Language Models","created":"2025-09-26","cited_by_count":2,"area":"mllm"},{"id":"2510.16712","title":"The Chameleon Nature of LLMs: Quantifying Multi-Turn Stance Instability in Search-Enabled Language Models","created":"2025-10-19","cited_by_count":2,"area":null},{"id":"2510.22102","title":"Mitigating Coordinate Prediction Bias from Positional Encoding Failures","created":"2025-10-25","cited_by_count":2,"area":"mllm"},{"id":"2603.04464","title":"Understanding the Dynamics of Demonstration Conflict in In-Context Learning","created":"2026-03-03","cited_by_count":2,"area":"mechinterp"},{"id":"2603.16941","title":"The Voice Behind the Words: Quantifying Intersectional Bias in SpeechLLMs","created":"2026-03-15","cited_by_count":2,"area":null},{"id":"2607.07678","title":"How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization","created":"2026-07-08","cited_by_count":2,"area":null},{"id":"2411.11424","title":"Membership Inference Attack against Long-Context Large Language Models","created":"2024-11-18","cited_by_count":1,"area":"safety"},{"id":"2506.23743","title":"Positional Bias in Binary Question Answering: How Uncertainty Shapes Model Preferences","created":"2025-06-30","cited_by_count":1,"area":null},{"id":"2507.14849","title":"Beyond Isolated Capabilities: Bridging Long CoT Reasoning and Long-Context Understanding","created":"2025-07-20","cited_by_count":1,"area":"lr"},{"id":"2507.17788","title":"Adaptive Repetition for Mitigating Position Bias in LLM-Based Ranking","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2510.09770","title":"GOLD PANNING: Strategic Context Shuffling for Needle-in-Haystack Reasoning","created":"2025-10-10","cited_by_count":1,"area":"lr"},{"id":"2601.04098","title":"Layer-wise Positional Bias in Short-Context Language Modeling","created":"2026-01-07","cited_by_count":1,"area":null},{"id":"2603.02225","title":"Scaling Reward Modeling without Human Supervision","created":"2026-02-11","cited_by_count":1,"area":"alignment"},{"id":"2604.19777","title":"Self-Describing Structured Data with Dual-Layer Guidance: A Lightweight Alternative to RAG for Precision Retrieval in Large-Scale LLM Knowledge Navigation","created":"2026-03-28","cited_by_count":1,"area":null},{"id":"2605.00445","title":"The Power of Order: Fooling LLMs with Adversarial Table Permutations","created":"2026-05-01","cited_by_count":1,"area":null},{"id":"2605.00505","title":"LLM-Oriented Information Retrieval: A Denoising-First Perspective","created":"2026-05-01","cited_by_count":1,"area":"rag"},{"id":"2605.11591","title":"Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration","created":"2026-05-12","cited_by_count":1,"area":"mllm"},{"id":"2605.11974","title":"Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization","created":"2026-05-12","cited_by_count":1,"area":null},{"id":"2606.13550","title":"Uncertainty-Aware Hybrid Retrieval for Long-Document RAG","created":"2026-06-11","cited_by_count":1,"area":"rag"},{"id":"2608.10908","title":"Order Matters: LVLMs as Judges for Temporal Reasoning in Image Sequences","created":"2026-08-11","cited_by_count":1,"area":"lr"},{"id":"2507.10088","title":"Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering","created":"2025-07-14","cited_by_count":0,"area":"synth"},{"id":"2603.19203","title":"Tinted Frames: Question Framing Blinds Vision-Language Models","created":"2026-03-19","cited_by_count":0,"area":"lr"},{"id":"2605.05594","title":"The Cost of Context: Mitigating Textual Bias in Multimodal Retrieval-Augmented Generation","created":"2026-05-07","cited_by_count":0,"area":"mllm"},{"id":"2606.14672","title":"Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows","created":"2026-06-12","cited_by_count":0,"area":"agents"},{"id":"2606.30219","title":"EvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety Failures","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2607.19358","title":"LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning","created":"2026-05-29","cited_by_count":0,"area":"lr"},{"id":"2608.26762","title":"Equal Ranking Quality, Different Decisions: Measuring and Reducing Order Dependence in LLM Scorers","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.18282","title":"Too Good to Be Real? Diagnosing and Reducing the Gap Between AI Preference and Real User Engagement","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.29278","title":"Reasoning Instructions Can Break Answer Decoding in Vision--Language Models","created":"2026-09-24","cited_by_count":0,"area":"lr"},{"id":"2610.03531","title":"Author Representation Strategies for Zero-Shot Authorship Attribution: A Comparative Study of LLM-Based and Embedding-Based Approaches","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.18233","title":"Consider, Then Choose: Order-Invariant Decisions in System One Models","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}