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9,568 papers
This work introduces PULSE (Paired Utility Localization over Sparse Encodings), an SAE-based framework for identifying model-internal features associated with demonstration utility and using them for demonstration selection, and PULSE-Retriever, which converts its magnitude into a feature-relevance mask for scalable po...
ForkLeft, a distillation framework that resolves a fundamental mismatch between autoregressive teacher predicts from a left prefix and NTP teacher under the same context, is introduced, showing that DLMs can learn NTP-style reasoning without sacrificing native parallel generation.
Agentsensus, a story-world simulation framework in which there is an unified long-term memory, is presented and is the only design whose memory becomes shared and linked, at judged simulation quality indistinguishable or even better than the baselines.
This work proposes PROUR, a proactive uncertainty routing framework that decomposes action uncertainty into disagreement across plausible user-goal interpretations, which signals user-side ambiguity, and the entropy remaining within each interpretation, which signals missing world-side evidence.
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The proposed EngramRAG is an adaptive memory architecture coupling a low-latency Waking State reflex with an asynchronous background Dreaming State consolidation cycle, and introduces triple-source hybrid retrieval fusing dense vectors, BM25, and U-PPR via dynamic Reciprocal Rank Fusion (RRF).
Large Language Models (LLMs) perform well on medical examinations and question-answering benchmarks, but remain unreliable on medical calculation tasks that require exact numerical outputs. These calculations support high-stakes decisions such as medication dosing, organ-function assessment, and prognostic scoring, for...
Choir is an open protocol for distributed formalization that decomposes a project into tasks that can be completed by independent contributors, each running their own agent with their own LLM subscription, while coordinating entirely through the project's GitHub repository.
This work introduces a failure-driven adaptation recipe spanning continued pre-training (CPT) and supervised fine-tuning (SFT) and formalizes an evidence-gated constraint-evaluation interface enforcing three-valued logic where unverified product evidence remains unknown rather than satisfied.
UniSandbox, a decoupled evaluation framework paired with controlled, synthetic datasets to avoid data leakage and enable detailed analysis, reveals a significant understanding-generation gap, which is mainly reflected in two key dimensions: reasoning generation and knowledge transfer.
This paper comprehensively studies effective prompt injection attacks against 14 widely used open-source and three closed-source LLMs on five attack benchmarks and proposes a straightforward and effective hypnotism attack, showing that this attack causes aligned language models to generate objectionable behaviors.
We present a fully automated pipeline that transforms large collections of court decisions into legal commentaries for statutes - without providing any handcrafted doctrinal framework. Using 4.555 decisions of the German Federal Court of Justice that cite sections 242, 280, 812 and 823 of the German Civil Code (BGB), w...
Direct Preference Optimization (DPO) is applied to align models, constructing preference pairs in which chosen responses preserve mixed-language content while rejected responses mimic failure patterns, suggesting DPO can effectively elicit correct code-switching transcription behavior from multilingual Audio LLMs.
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Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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