113 citations · 1k across the 66 of their papers we have counts for
70 papers
Audio LLMs Know When They Can't Hear You
Amirhosein Javadi, Richa Dixit, Mehrdad Farajtabar +3
Audio large language models allow users to interact with the model through speech. When an input recording is too degraded, the model may misinterpret the user's query and respond…
Efficient Mixture-of-Experts with Speculative Decoding via Expert Coactivation
Kumari Nishu, Han-Byul Kim, Santosh Chilkunda +13
Mixture-of-Experts (MoE) models are increasingly deployed alongside Speculative Decoding (SD) to accelerate inference, but combining the two is challenging. SD improves the inferen…
Self-Compacting Language Model Agents
Tianjian Li, Jingyu Zhang, William Jurayj +5
Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaf…
TIDE: Every Layer Knows the Token Beneath the Context
Ajay Jaiswal, Lauren Hannah, Han-Byul Kim +3
We revisit a universally accepted but under-examined design choice in every modern LLM: a token index is looked up once at the input embedding layer and then permanently discarded.…
Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why
Mohammadreza Armandpour, Fatih Ilhan, David Harrison +6
On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this signal is beneficial and under whi…
Recursive Language Models Meet Uncertainty: The Surprising Effectiveness of Self-Reflective Program Search for Long Context
Keivan Alizadeh, Parshin Shojaee, Minsik Cho +1
Long-context handling remains a core challenge for language models: even with extended context windows, models often fail to reliably extract, reason over, and use the information…