Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. However, Multi-hop Question Answering (MHQA) remains challenging for many existing models due to issues like hallucination, error propagation, and limited context length. To...
Xiaochen Wang, Liang Chen, Reza Haf Zhe Yang et al.· 0 citations
A novel defense method called Eraser is proposed, which mainly includes three goals: unlearning harmful knowledge, retaining general knowledge, and maintaining safety alignment, which can significantly reduce the jailbreaking success rate for various attacks without compromising the general capabilities of the model.
Wei-Kai Lu, Zi-Qian Zeng, Jian-Wei Wang et al.· arXiv.org· 61 citations· ⚡11
Authorship identification uses patterns in writing to infer who wrote a text, but those patterns also reflect topic, genre, and register. This survey argues that topic-independence is not a property of a stylistic feature but of the feature together with its encoding, its scoring rule, and the evaluation split, so the...
The natural language generation domain has witnessed great success thanks to Transformer models. Although they have achieved state-of-the-art generative quality, they often neglect generative diversity. Prior attempts to tackle this issue suffer from either low model capacity or over-complicated architectures. Some rec...
Yueen Ma, Dafeng Chi, Jingjing Li et al.· 0 citations
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This work introduces Harness-Zero, which enables harness distillation through agent-as-harness, and shows that for frontier LLMs using the same evolved harness, agent-as-harness outperforms code-as-harness.
Hao-Ran Ye, Yuxing Lu, Hao-Nan Dong et al.· 5 citations· ⚡1
LLM agents are increasingly deployed in collaborative settings, yet long-term interaction may give rise to undesirable coordination. We study the emergence of collusion in a long-horizon multi-agent environment: two agents repeatedly complete individual tasks, share task logs, verify each other's work, and receive rewa...
SLICEChat is introduced, a slide-level MLLM that integrates progressive token pruning within a hybrid Mamba--Transformer slide encoder, which demonstrates accurate and computationally efficient multimodal reasoning over gigapixel WSIs.
Ali Kerem Bozkurt, Baris Cem Bakay, Ibrahim Kulac et al.· 0 citations
Argumentative component detection (ACD) is a core subtask of Argument(ation) Mining (AM) and one of its most challenging aspects, as it requires jointly delimiting argumentative spans and classifying them into components such as claims and premises. While research on this subtask remains relatively limited compared to...
Sofiane Elguendouze (UniCA, I3S, MARIANNE) et al.· 0 citations
HyperQ is introduced, which adds token-conditioned quantum residual branches to a frozen masked-diffusion language model, and support token-conditioned circuit emission as a tractable architectural approach to quantum-augmented language modelling.
Xiaoqiang Wang, Meng-Yang Xiong, Jun Dai et al.· 0 citations
The results show where domain specialization and lightweight adaptation offer practical value, and where transformer accuracy justifies higher inference costs, providing an empirical basis for building knowledge systems under resource constraints.
Genis Skura, A. Geissbühler, Jean-Luc Falcone· 0 citations
Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case. Existing PCR benchmarks and methods predominantly operate at the document level, treating entire judgments as the unit of relevance. This formulation is suboptimal for legal practitioners, as judgments address multiple legal iss...
Text-to-speech models for Bantu tonal languages are challenged by a tonal system that is rooted in both the lexis (i.e., the inventory of words, stems, and affixes) and the grammar (i.e., morpho-syntax). To complicate matters, the standard writing systems of these languages often omit tone markings and syllable duratio...
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.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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