At 460 h of clean LibriSpeech, the seed moves fairness metrics more than compression does on most demographic axes, and a balanced 3x3 decomposition attributes 85.3% of the variation in Fair-Speech ethnicity normalized gap to the seed against 8.3% to compression.
Srishti Ginjala, E. Fosler-Lussier, Srinivasan Parthasarathy· 0 citations
GraphForge, an evidence-graph based framework that grounds both the task and its verification in real files, and rejects fine-tuning on the SFT model's own rollouts yields further improvements on all three benchmarks, suggesting that the rubrics provide a useful selection signal.
Qi-Sheng Su, Han-Chen Wang, Guang Zhu et al.· 0 citations
Finding a relevant paper is not the same as producing a verifiable answer from it. LitTraceQA requires canonical paper identifiers, exact evidence at the page or object level, and typed answers that match the evaluator. We call the separation between source access and scorer-visible correctness the grounding contract g...
Model-attribution classifiers can often identify which language model produced a text, making model-specific writing patterns a signal of provenance. Accurate attribution on unmodified text, however, does not show whether the prediction still identifies the original source after deliberate rewriting. We formulate this...
Hao-Han Yuan, Si-Min Chen, Xi Niu et al.· 0 citations
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It is established that principled and informed team selection is critical and strong model selection algorithms for assembling effective multi-LLM systems are presented.
Zong-Wan Cao, Zi-Yuan Yang, Shang-Bin Feng et al.· 0 citations
Overlap-Unique-Conflict (OUC) extraction, a cross-narrative task that extracts all overlapping, conflicting, and unique clauses from two narratives, is introduced, finding that unique information is far easier to extract than overlap and conflict.
Steering large language models typically relies on linear, context-independent interventions in activation space, an assumption that recent work has challenged and that can induce an information bottleneck when a fixed representation must encode many behavioral distinctions. We introduce MetaSteer, a method that learns...
A multilingual named-entity tagger with fine-grained distinctions supporting varied redaction policies and methods for cheaply learning additional distinctions is developed, and a multilingual encoder with an affine span-tagging head is fine-tuned for frontier-model annotations in 35 languages.
Yor\`ub\'a is a tonal language in which contour tones pose persistent orthographic challenges. These are especially notable for personal names and lexical items whose conventional spellings avoid vowel lengthening that would otherwise provide a host syllable for the second tone. A particular concern is a class of names...
Language models increasingly make real-time decisions in applications that apply the latest answer until a newer one arrives. A late answer can prolong an outdated decision, such as a call recorder still running while a customer reads out card details, an error offline accuracy misses. We make three contributions. Firs...
Speculative decoding accelerates autoregressive LLMs by having a lightweight drafter propose tokens that the target model verifies in parallel. Diffusion-based drafters further reduce drafting latency by proposing multiple tokens at once. However, these tokens are predicted independently, so a single early error causes...
Long-Xuan Yu, Bingsen Chen, Peng Shi et al.· 0 citations
Access to real-world information is often noisy and fragmented. Constructing a coherent narrative from such fragments requires models to reconstruct missing spans within a broader storyline, commonly referred to as text infilling, while preserving consistency with both the local context and the global storyline. Despit...
Eftekhar Hossain, John Salvador, Santu Karmaker· 0 citations
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
MIT News · Artificial Intelligence· news.mit.eduAug 31, 2026
With millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.