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Computation & Language / NLP
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TokenGate: Adapting LLMs for Fast and Memory-Efficient Prefill with Learned Token Pruning
Expert human readers process large inputs (e.g., code repositories and long documents) by skimming to closely read only what matters.HarnessPro: Recursive Harness Self-Improvement with Pareto Optimization for Performance-Cost Trade-offs
Harness development plays a crucial role in building capable AI agents.Monsoon: Scalable Spontaneous Speech Collection for Low-Resource ASR in 50 Languages
For most languages, automatic speech recognition (ASR) is limited less by model architecture than by a lack of accurately transcribed spontaneous speech.Game of Phones: Harnessing Game Theory and LLMs in 'Bot Wars' to Counteract Phone Scams
Phone scams impose substantial and growing costs on individuals and financial systems worldwide, yet existing countermeasures impose no resource cost on perpetrators.RESIN: Multi-Chain Reasoning with Entity-Structured Indexing
Multi-chain reasoning is a challenging task not only because the multi-chain evidence is dispersed, but also because different parts of reasoning may require distinct, interacting chains of support.Teacher Supervision, Fixed Representations and Calibration: Exact Risk Calculations for Candidate-Scoring Decision Models
Candidate-scoring decision models return a probability distribution over a presented set of answers.Safety Mid-Training: Internalizing LLM Safety as a Foundational Capability
Safety alignment for large language models (LLMs) is primarily performed during post-training, while recent work has also begun incorporating safety data into pre-training.ASTOR: Benchmarking and Improving Autoformulation for Soft-Constraint Optimization with a Formal Grammar
Real-world decision problems combine two qualitatively different kinds of constraints: requirements that must be satisfied, called hard constraints, and preferences that can be violated, called soft…AfriBED: a Speech Recognition Bias Evaluation Dataset for Low Resource African Languages
Despite advancements in automatic speech recognition systems (ASR), current systems exhibit speaker-attribute bias, i.e., their speech recognition performance is biased against certain speakers…SpecMRL: Redesign Matryoshka Representation Learning within Parametric Spectrum
Matryoshka Representation Learning (MRL) is designed to support flexible representation sizes by jointly optimizing nested prefixes.MemT-1.0: Towards Memory-Native Evolution
Memory-native evolution requires making memory an intrinsic capability of foundation models, enabling them to continuously accumulate and utilize information.RefCraft: Benchmarking Visual-Reference-Conditioned Agentic Generation through Web Development
Beyond basic tool use and coding skills, effectively incorporating visual references into agentic generation is equally essential for applying AI agents to real-world productivity tasks.KEEP-Bench: Evaluating Evidence Preservation in Context Compression
Context compression improves long-context efficiency but may introduce faithfulness issues through an information bottleneck.Agent World Model in the Wild: Computer-Use Agent Environment Synthesis
Agent learning is shifting from learning from human data toward learning through interaction with the world.Competing Learning in Hybrid Architectures
Many modern language models have adopted hybrid architectures that incorporate both linear-time recurrence and softmax attention.LatComm: Reusable Context Compression for Latent Communication between Large Language Models
Systems that combine several large language models (LLMs) often use one context for many questions.WeAct: Dynamic Weight Switching as Agent Actions
Long-horizon agents must learn heterogeneous capabilities from interleaved trajectories.OpenVLHarness: Real World Visual Agentic Tool-Use with Multimodal Memory
Multimodal large language models (MLLMs) have made rapid progress on visual reasoning, yet many tasks require evidence that is difficult to obtain through internal reasoning alone: our controlled…Can It Actually Work? Synthesizing Functional CAD Mechanisms
While LLM agents can generate visually plausible CAD assemblies, these designs often fail to fulfill their intended physical functions.Think Before You Transcribe: Context-Steered Reasoning for Hotword-Aware Speech Recognition
Contextual automatic speech recognition (ASR) improves rare-entity recognition by supplying candidate hotwords, but retrieved candidates may be incomplete or incorrect.