14 papers
MemTrace: Probing What Final Accuracy Misses in Long-Term Memory
Xianxuan Long, Zhikai Chen, Shenglai Zeng +3
LLM agents increasingly maintain long-term memory of user facts across sessions. Yet such memory is usually evaluated by aggregating accuracy over question rows or episodes. Becaus…
Magnifying What Matters: Attention-Guided Adaptive Rendering for Visual Text Comprehension
Shenglai Zeng, Qirui Wang, Kai Guo +3
Visual Text Comprehension (VTC) renders text into images for a vision-language model (VLM) to read, sidestepping LLM context-window limits and powering applications from long-page…
OpenRFM: Dissecting Relational In-Context Learning
Zhikai Chen, Junyu Yin, Jialiang Gu +5
Relational Foundation Models (RFMs) promise a single pre-trained predictor that, given any relational database, returns predictions in one forward pass via relational in-context le…
Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline
Zhikai Chen, Jialiang Gu, Junyu Yin +6
LLM agents accumulate histories that outgrow their context windows, motivating a growing literature on memory systems. Yet most existing designs are tuned to a single scenario (mul…
When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
Xinnan Dai, Kai Yang, Cheng Luo +3
Reasoning hallucinations in large language models (LLMs) often appear as fluent yet unsupported conclusions that violate either the given context or underlying factual knowledge. A…
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
Haoyu Han, Li Ma, Yu Wang +9
Retrieval-Augmented Generation (RAG) improves large language models (LLMs) by retrieving relevant information from external sources and has been widely adopted for text-based tasks…