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#RAG

MemSifter: Offloading LLM Memory Retrieval via Outcome-Driven Proxy Reasoning

Intermediate

Jiejun Tan, Zhicheng Dou et al.Mar 3arXiv

MemSifter is a smart helper that picks the right memories for a big AI so the big AI doesn’t have to read everything.

#long-term memory#LLM retrieval#proxy model

LaSER: Internalizing Explicit Reasoning into Latent Space for Dense Retrieval

Intermediate

Jiajie Jin, Yanzhao Zhang et al.Mar 2arXiv

LaSER teaches a fast search model to “think” quietly inside its hidden space, so it gets the benefits of step-by-step reasoning without writing those steps out as text.

#dense retrieval#chain-of-thought#latent reasoning

Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning

Beginner

Chris Samarinas, Haw-Shiuan Chang et al.Feb 26arXiv

SLATE is a new way to teach AI to think step by step while using a search engine, giving feedback at each step instead of only at the end.

#retrieval-augmented reasoning#reinforcement learning#GRPO

MMA: Multimodal Memory Agent

Intermediate

Yihao Lu, Wanru Cheng et al.Feb 18arXiv

Long-horizon AI assistants can grab old, low-quality, or conflicting memories and then answer with too much confidence, which is dangerous.

#memory-augmented LLMs#multimodal agents#reliability scoring

LiveMedBench: A Contamination-Free Medical Benchmark for LLMs with Automated Rubric Evaluation

Beginner

Zhiling Yan, Dingjie Song et al.Feb 10arXiv

LiveMedBench is a new, always-updating test for medical AIs that keeps test questions safely separated from training data to avoid cheating by memorization.

#LiveMedBench#medical benchmark#data contamination

OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent

Intermediate

Bowen Yang, Kaiming Jin et al.Jan 12arXiv

Computer-using agents kept forgetting important visual details over long tasks and could not reliably find up-to-date, step-by-step help for unfamiliar apps.

#computer-using agents#vision-language models#milestone memory

Memory Matters More: Event-Centric Memory as a Logic Map for Agent Searching and Reasoning

Intermediate

Yuyang Hu, Jiongnan Liu et al.Jan 8arXiv

This paper turns an AI agent’s memory from a flat list of notes into a logic map of events connected by cause-and-time links.

#event-centric memory#Event Graph#logic-aware retrieval