We replicate the distributional-semantics extractive summarisation method of Mohd, Jan and Shah (2020) and adapt it to Hindi, substituting a Devanagari-appropriate component at every language-specific step. The system is evaluated on two independent corpora --- the Hindi portion of XL-Sum and FIRE ILSUM 2.0 Hindi --- u...
Showket Ahmad Khan, Mudasir Mohd, Nasrullah Sheikh et al.· 0 citations
Emotion dynamics are critical for understanding crisis-support conversations, yet most computational work treats emotion as static utterance-level labels. We introduce EMPATH, a framework for understanding affective dynamics in mental health dialogues across three granularities: turn-level labels, transition probabilit...
Ziwei Gong, Yu-Chen Huang, Wen Liang et al.· 0 citations
This work proposes an LLM chaining architecture that separates instruction classification and action generation into two specialized stages, reducing per-inference prompt length by approximately 45% while improving planning consistency.
Lucas Da Mota Bruno, Jiahao Sim, Y. Hagiwara· 0 citations
This work identifies a failure mode not addressed by a stronger model: when the context contains an assertion by a party with an incentive toward optimism - here the sales representative, a witness recorded in the CRM - the model treats the assertion as evidence and clears deals the company's own records deem unaccepta...
Rahul Balakavi· 0 citations
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A language model's confidence in an answer is often read as a proxy for how well it knows the corresponding fact. This manual documents an open toolkit built to test that reading directly: a small causal language model is fine-tuned on a corpus that consistently asserts one fabricated arithmetic answer for each of the...
Jos\'e Luciano Ver\c{c}osa Marques, Frederico Jorge Heitmann, Daniel Omar Perez et al.· 0 citations
The results demonstrate that multilevel evaluation improves the reliability that the proposed framework effectively balances performance and efficiency, which makes the framework suitable for practical hate speech moderation systems that require accurate, generalizable, and explainable decisions.
Rameesha Zia, Muhammad Shahid Iqbal Malik· 0 citations
Post hoc explanation methods such as SHAP and LIME are widely used to interpret text classifiers, but their visualizations are mainly designed for left-to-right languages. When applied to right-to-left (RTL) languages such as Urdu, Arabic, Persian, and Hebrew, the attribution values remain mathematically valid, while t...
Rameesha Zia, Muhammad Shahid Iqbal Malik· 0 citations
ExplorationBench turns the wicked problem of evaluating scientific exploration into a concrete and tractable framework built on verifiable Alien Worlds, and finds that the strongest systems can acquire and apply unfamiliar rules, while performance varies substantially across trajectories and continued exploration can s...
Ming Zhang, Zhen Xiang, Pei-Zhong Gao et al.· 0 citations
Empirical evaluations show that GRASP consistently establishes a new state-of-the-art frontier across diverse datasets, yielding substantial accuracy gains over direct LLM planners on Natural Plan Calendar Scheduling, ZebraLogic, and SciBench Math.
Arunabh Srivastava, M. Khojastepour, Srimat T. Chakradhar et al.· 0 citations
Simulation made broad exploration of models, reasoning settings, and prompts feasible without customer exposure, enabling production improvements that would have been impractical to pursue through live experimentation alone.
Edesio Alcoba, Kevin Rossell, Aman Gupta et al.· 0 citations
PrivDrift is introduced, a benchmark for auditing whether user-disclosed secrets remain recoverable after conversational topic drift and persuasion-based probing, suggesting that privacy risk in active LLM contexts should be evaluated as a persistent behavioral failure mode rather than only as training-data memorizatio...
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.
MIT News · Artificial Intelligence· news.mit.eduSep 24, 2026
