Realm
PulseAugur coverage of Realm — every cluster mentioning Realm across labs, papers, and developer communities, ranked by signal.
- 2026-05-14 research_milestone Publication of a new framework for LFP decoding in BCIs. source
1 day(s) with sentiment data
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New research benchmarks LLM agent efficiency, robustness, and safety · 10 sources tracked
Multiple research papers released on arXiv explore advancements in Large Language Model (LLM) agents, focusing on improving their efficiency, robustness, and safety. SpecCompact accelerates LLM agent context compaction …
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New REALM framework enables causal LFP decoding for brain-computer interfaces
Researchers have developed REALM, a novel framework for causal local field potential (LFP) behavior decoding. This retrospective knowledge distillation approach transfers representational knowledge from a non-causal "te…
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Architectural Retrieval: A New Paradigm for LLMs
Architectural retrieval methods embed document lookups directly into a model's architecture, differing from standard RAG which pastes retrieved text into the prompt. This approach aims to reduce attention costs and impr…
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New REALM benchmark unifies VLM red-teaming for physical-world safety
Researchers have introduced REALM, a novel benchmark designed to evaluate the vulnerabilities of physical-world Vision-Language Models (VLMs). This benchmark unifies 12 red-teaming methods, 3 defenses, and 13 VLMs under…
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New framework ReaLM fuses KG embeddings with LLMs; study finds KG embedding models unstable
Researchers have developed ReaLM, a new framework that bridges the gap between knowledge graph embeddings and large language models by discretizing KG embeddings into learnable tokens. This approach allows for a more ef…
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REALM framework enables real-time LFP decoding for BCIs
Researchers have developed REALM, a new framework for real-time decoding of local field potentials (LFPs) in brain-computer interfaces. This method uses a retrospective distillation process to transfer knowledge from a …
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REALM framework aligns RGB and event camera data for cross-modal perception
Researchers have developed REALM, a novel cross-modal framework designed to align RGB and event camera data within a shared latent manifold. This approach projects event representations into the latent space of pre-trai…