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Evolving Long-Term Memory

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Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory

Announce Type: new Abstract: In existing memory benchmarks for Large Language Models (LLMs), the evaluated dialogue sessions often lack long-term semantic consistency, and the underlying personas tend to be flat and static. Furthermore, in real-world scenarios, interactions between users and assistants involve more diverse, heterogeneous data streams, such as documents and emails. These shortcomings significantly limit the realism and effectiveness of current evaluations.

arXiv CS 9d ago

Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory

arXiv:2605.31086v2 Announce Type: replace Abstract: In existing memory benchmarks for Large Language Models (LLMs), the evaluated dialogue sessions often lack long-term semantic consistency, and the underlying personas tend to be flat and static. Furthermore, in real-world scenarios, interactions between users and assistants involve more diverse, heterogeneous data streams, such as documents and emails. These shortcomings significantly limit the realism and effectiveness of current evaluations.

arXiv CS 8d ago

Memory Beyond Recall: A Dual-Process Cognitive Memory System for Self-Evolving LLM Agents

Announce Type: new Abstract: Long-term memory for an LLM agent is more than retrieving the right passage at the right time. Current memory systems collapse belief revision, causal coupling, and cross-domain abstraction into a single retrieval surface tuned for surface recall, and consequently struggle on implicit personalisation that requires reasoning over how a user has evolved. We propose DCPM, which reorganises agent memory along a cognitive capability hierarchy ascending from raw inputs...

arXiv CS 1d ago

RGMem: Renormalization Group-inspired Memory Evolution for Language Agents

arXiv:2510.16392v3 Announce Type: replace Abstract: Personalized and continuous interactions are critical for LLM-based conversational agents, yet finite context windows and static parametric memory hinder the modeling of long-term, cross-session user states. Existing approaches, including retrieval-augmented generation and explicit memory systems, primarily operate at the fact level, making it difficult to distill stable preferences and deep user traits from evolving and potentially...

arXiv CS 7d ago

Deep learning four decades of human migration

Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...

Nature 1d ago

Chinese memory makers step up challenge to Korea’s chip champions

Chinese memory makers step up challenge to Korea’s chip champions CXMT and YMTC are nearing public listings, giving China’s memory-chip sector fresh firepower in its pursuit of Samsung and SK Hynix This article was first published by The Korea Times in a partnership with the South China Morning Post. Two of China’s leading memory-chip makers are moving closer to public listings, posing a significant long-term challenge to South Korean giants Samsung Electronics and SK Hynix, despite a...

South China Morning Post 4d ago

Fear of recurrence: How immune memory helps cancer survivors face their worst nightmare

Every year the world observes National Cancer Survivors Month in June, celebrating the growing number of people who have successfully completed cancer treatment and are building lives beyond their diagnosis. For many survivors, however, the end of treatment does not always bring complete peace of mind. Even years later, routine scans, follow-up appointments or unexplained aches can revive a lingering question: What if the cancer comes back?

Times of India 1d ago

AutoSci: A Memory-Centric Agentic System for the Full Scientific Research Lifecycle

Announce Type: new Abstract: Scientific research has traditionally been human-intensive, requiring researchers to coordinate literature, ideas, experiments, manuscripts, and review responses across long project cycles. The rise of LLM-based scientific agents creates an opportunity to automate this process. Such a system must support the full research lifecycle, maintain structured persistent memory across projects, and improve its own research procedures over time.

arXiv CS 9d ago

Analysis:How a nudge from Nvidia propelled frugal Micron into the AI boom and a $1 trillion market cap

Analysis:How a nudge from Nvidia propelled frugal Micron into the AI boom and a $1 trillion market cap SAN FRANCISCO, June 2 : Micron Technology's march toward a $1 trillion valuation is nothing if not dramatic: a year ago it was a little over $100 billion. That surge, though, was not built on its famed frugality, but on a nearly too-late push from Nvidia that pulled the U.S. memory chipmaker into the center of the AI boom. For decades, the Idaho-based company survived by building factories...

Channel News Asia 8d ago

HighTide: An Agent-Curated Open-Source VLSI Benchmark Suite

arXiv:2606.04126v1 Announce Type: new Abstract: We introduce HighTide, an evolving AI-assisted benchmark suite. Specifically, the contributions are: (i) a diverse open-source suite spanning multiple design languages and technology nodes, (ii) Bazel-based incremental RTL-to-GDS compilation with remote caching, (iii) AI-assisted design curation through twelve agent skills covering the design lifecycle, flow optimization, tool reference, and meta-maintenance, backed by per-design decision logs...

arXiv CS 6d ago